AN ANALYSIS OF THE SOCIO-ECONOMIC AND SOCIO- DEMOGRAPHIC CONTRIBUTORS TO PROPERTY CRIME IN THE LOWER MAINLAND DISTRICT

Dr. Irwin M. Cohen, Dr. Garth Davies, Kevin Burk, and Christine Neudecker

August 2016

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IntroductionAccordingtothedatapresentedbypoliceleadersattheSeptember29th,2015MetroVancouverCrimeMeeting,propertycrimeincreasedforthesecondconsecutiveyearintheLowerMainlandDistrict(LMD)ofBritishColumbia.Ofthe22RCMPandmunicipalpolicejurisdictionsthatcomprisetheLMD,itwasreportedthat,betweenJanuaryandAugust2015,13hadexperiencedanincreaseintheirpropertycrimeratesoverthepreviousyear,andthatthistrendwasacontinuationofthetrendthatsawageneralincreaseinpropertycrimeratesin2014from2013.Notsurprisingly,thesuddenincreaseinpropertycrimeoverthepasttwoyearshasresultedinasearchforexplanations.

Severallinesofinquirymustbeconsideredtobetterunderstandpropertycrime.Inparticular,attentionmustbepaidtothecontextualdifferencesthatdifferentiatenotjustonemunicipalityfromother,butalsothedifferentneighbourhoodswithinthesamemunicipality,whichvarysignificantlyintermsoftheirlevelsofcrime.Totalkaboutpropertycrimeinacityasawholemaymaskimportantvariationsacrosscommunitiesandneighbourhoods.Givenwhatresearchhasfoundinothercities,itispossiblethattheeffectsofsocio-demographicandsocio-economicfactorsvarymorewithincitiesthanbetweencities.Giventhis,thefocusofthisreportincludesa)howeachmunicipalityintheLowerMainlandDistrictcomparestoeachother,andb)identifyingthe“neighbourhoodeffects”thatalsocontributetofluctuationsinpropertycrimewithinsinglemunicipalities.TheoverallpurposeofthisreportistoexaminepropertycrimeintheLMDandprovideatheoreticalandempirical-basedassessmentofthesocio-economicandsocio-demographicvariablesthatmightbecontributingtotheincreaseinpropertycrimeratesoverthepasttwoyears.

ContextofPropertyCrimeintheLowerMainlandDistrictWhilethereisajustifiableconcernovertheincreaseinthenumberofpropertycrimesintheLMDsince2014,itisimportanttonotethat,forthemostpart,thepropertycrimerateconsistentlydroppedyearoveryearbetween2001and2013intheLMD.AsdemonstratedinFigure1,basedonStatisticsCanada’saggregatedpropertycrimeratesfortheVancouvercensusarea1,propertycrimeratespeakedin2003,but,overall,decreasedfrom8,630propertycrimesper100,000peoplein2001to4,647propertycrimesin2013;adecreaseof46.2%.AlthoughtheVancouvercensusareasawanincreaseof11.4%initspropertycrimeratein2014from2013,overall,between2001and2014,theVancouvercensusarea’spropertycrimeratedecreasedby39.3%.

SimilartothepatternfortheVancouvercensusarea,asdemonstratedinFigure1,theAbbotsford-Missioncensusarea’spropertycrimeratepeakedin2004,witharateof9,572propertycrimesper

1TheVancouverCensusAreaincludesVancouver,Surrey,Burnaby,Richmond,Coquitlam,Langley,Delta,NorthVancouver,MapleRidge,NewWestminster,PortCoquitlam,WestVancouver,PortMoody,WhiteRock,andPittMeadows.

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100,000people,but,overall,decreasedfrom8,829propertycrimesper100,000peoplein2001to4,072propertycrimesin2013;adecreaseof53.9%.LiketheVancouvercensusarea,theAbbotsford-Missioncensusareaalsosawanincreaseinitspropertycrimeratein2014from2013of6.6%;however,overall,between2001and2014,theAbbotsford-Missioncensusarea’spropertycrimeratedecreasedbyanimpressive50.6%.Onecontributingfactorthatmayhelpexplainthissubstantialdeclineinpropertycrimemaybethepolice’sadoptionofacrimereductionstrategyintheLMD.

FIGURE1:PROPERTYCRIMERATESBYCENSUSAREA(2001–2014)2

Whiletherehavebeensomeyearswithonlysmalldecreases,orevenslightincreasesinthepropertycrimerate,itisimportanttorecognizethatpropertycrimeratesaremuchlowertodaythantheywerein2000ineverysingleLowerMainlandDistrictjurisdiction.However,evenwiththissubstantialoveralldecreaseinpropertycrimeratesintheLowerMainlandDistrictoverthepast14years,severalcities,aswellasthelargerVancouverandAbbotsford-Missioncensusareas,haveseenaslightincreaseinthepropertycrimeratestartingaround2013.

Somejurisdictions,includingAbbotsford,Mission,Chilliwack,andHope(seeFigure2),sawincreasesinpropertycrimeratesbeginningin2000;however,thepeakyearforpropertycrimeinHope,Abbotsford,andChilliwackwas2003,whilethepeakyearforMissionwas2002.Moreover,theslopeofthedeclinewassomewhatsimilarforChilliwackandAbbotsford.Incontrast,thereweresomewhatsmoothandconsistentdeclinesyearoveryear,whereasthedeclinesinMissionandHopeweresomewhatlessconsistentyearafteryear.Forexample,forHope,thepropertycrimerateincreasedsharplyfromarateof9,136per100,000peoplein2000to17,012in2003;an

2DatacollectedfromStatisticsCanadaCANSIMTable252-0081,June22,2016.

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increaseof86.2%,butthendeclinedsharplyto12,177by2005;adecreaseof28.4%.Thepropertycrimerateremainedvirtuallyunchangedin2006,butthenroseagainto15,040in2007,beforedroppingto7,764by2010;adecreaseof48.4%injustthreeyears.

WhilenotnearlyassubstantialasHope,Missionalsohadsomefluctuationsyearoveryear,unlikeAbbotsfordandChilliwack,whichhadsmall,butconsistentdeclinesyearoveryearfromtheirpeaksto2012.Thisisjustoneexampleofwhyitisimportanttonotjustcomparecitytocity,buttoconsiderwithincitydifferences,whichwillbethefocusofanothersectionofthisreport.Intermsoftheoveralldecreasesinthepropertycrimeratesbetween2000and2014fortheEasternFraserValley,thelargestdecreasewasseeninAbbotsford(-42.0percent)followedbyMission(-31.7percent),Hope(-30.4percent),andChilliwack(-19.8percent).

Ofnote,inthelastfewyears,Chilliwackexperiencedanincreaseinitspropertycrimerateeachyearsince2011,resultinginan11.2%increaseintheirpropertycrimeratefrom2011to2014,Abbotsfordalsohadanincreaseof10.6%between2012and2014,whileHopeandMissionhaveseentheirpropertycrimeincreaseby9.8%and5.0%respectivelysince2013.So,whileeachofthesejurisdictionshaveseenlargedecreasessince2000andevenlargerdecreasessincetheirpeakyears,inthepastcoupleyears,propertycrimerateshavebeguntoincreaseslightly.

FIGURE2:PROPERTYCRIMERATESFOREASTERNFRASERVALLEY(2000–2014)3

ThesamepatternemergedforthemunicipalitiesintheWesternFraserValley,whichincludedLangleyCity,LangleyTownship,Surrey,WhiteRock,Delta,MapleRidge,andPittMeadows.With

3DatacollectedfromStatisticsCanadaCANSIMTable252-0081,June22,2016.

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theexceptionofPittMeadowsandWhiteRock,alloftheotherjurisdictionssawanincreaseintheirpropertycrimeratebetween2000and2001(seeFigure3).Conversely,PittMeadowsexperiencedareductionintheirpropertycrimerateuntil2002,whileWhiteRock’spropertycrimeratebegantoincreasein2001.Regardless,by2003,alloftheWesternFraserValleyjurisdictionshadpeakedandthenexperienceddecreasesintheirpropertycrimeratesthatlasteduntilbetween2010and2014.However,severaldistinctpatternsemerged.Onepattern,demonstratedbyLangleyCity,LangleyTownship,andSurrey,involvedagenerallysmoothandconsistentdecreaseinthepropertycrimerateyearoveryear.Forexample,inSurrey,thepropertycrimeratedeclinedfromitspeakin2001of10,049propertycrimesper100,000peopletoalowof5,539in2010(-44.9percent)beforeincreasingslightlythrough2013andthensharplyin2014.Theincreasefrom2010to2014representeda26.6%increaseinSurrey’spropertycrimerate.Still,from2000to2014,propertycrimedecreasedinSurreyby22.5%.

LangleyCityandLangleyTownshipbothsawasteadydeclineintheirpropertycrimeratesthrough2008and2009respectively,beforediverging.ForLangleyTownship,thedeclinecontinueduntil2014,whentherewasanincreaseof18.7%fromthepreviousyear.Still,between2000and2014,thepropertycrimerateinLangleyTownshipdroppedby12.4%.LangleyCityhadasomewhatuniquepattern,asitspropertycrimerateincreasedveryslightlyfrom2008to2010(+3.5percent),declinedagainbetween2010and2011(-5.3percent),increasedagainbetween2011and2012(+11.4percent),beforedecreasingthrough2014(17.7percent).Ineffect,LangleyCitywastheonlyjurisdictionfromEasternandWesternFraserValleythatdidnotexperienceanincreaseinthepropertycrimeratein2014from2013.Moreover,overall,between2000and2014,thepropertycrimeratedroppedby30.1%inLangleyCity.

TheotherjurisdictionsintheWesternFraserValleyhadalessconsistentpatternwithyearoveryearincreasesanddecreases(seeFigure3).Nonetheless,allofthesejurisdictionsexperiencedtwothingsincommon,namely,anoveralldecreaseintheirpropertycrimeratesbetween2000and2014,andanincreaseintheirpropertycrimeratesin2014fromthepreviousyear.Forexample,Deltahadanoverallpropertycrimeratedecreaseof36.7%,buthadanincreaseof8.7%in2014fromthepreviousyear.MapleRidgehadanoverallpropertycrimeratedecreaseof37.9%,buthadanincreaseof34.8%in2014fromthepreviousyear.

Asmentionedabove,theotherinterestingfindingwasinPittMeadowsandWhiteRock.Inbothofthesejurisdictions,ratherthanseeingpropertycrimeratesincreasein2001from2000,aswascommonalloftheotherWesternFraserValleyandEasternFraserValleyjurisdictions,thesemunicipalitiessawdecreasesof19.0%and6.6%,respectively(seeFigure3).Inadditiontothesedecreases,theoveralldeclineinpropertycrimeratesforWhiteRockbetween2000and2014was33.8%,andthedecreaseinPittMeadowsoverthesametimeperiodwas33.6%.

Insummary,intermsoftheoveralldecreasesinthepropertycrimeratesbetween2000and2014fortheWesternFraserValley,thelargestdecreasewasseeninMapleRidge(-37.9percent),followedbyDelta(-36.7percent),WhiteRock(-33.8percent),PittMeadows(-33.6percent),LangleyCity(-30.1percent),Surrey(-22.5percent),andLangleyTownship(-12.4percent).

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FIGURE3:PROPERTYCRIMERATESFORWESTERNFRASERVALLEY(2000–2014)4

FortheGreaterVancouverArea,whichincludedCoquitlam,PortCoquitlam,PortMoody,NewWest,Richmond,Burnaby,Vancouver,andUBCVancouver,again,themaingeneralpatternsdiscussedabovewerefound(seeFigure4).Forexample,onetrendwasthatmostjurisdictionssawanincreaseintheirpropertycrimeratesin2001fromthepreviousyear,withtheonlyexceptionsbeingtheCityofVancouver,Coquitlam,andPortMoody.Also,allofthejurisdictionshadtheirpropertycrimeratespeakbetween2001and2005.

Asecondtrendinvolvedagenerallysmoothdecreaseinpropertycrimeratesyearoveryearfromtheirpeakyeartothebeginningoftheirrisingpropertycrimeratessometimeafter2011.Forexample,Coquitlam’speakyearforpropertycrimewas2003witharateof8,159propertycrimesper100,000people.Thisratedeclinedeachyearto2011,resultingina56.4%decreaseoverthattimeperiod(seeFigure4).However,between2011and2014,thepropertycrimerateincreasedby11.1%.

4DatacollectedfromStatisticsCanadaCANSIMTable252-0081,June22,2016.

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FIGURE4:PROPERTYCRIMERATESFORTHEGREATERVANCOUVERAREA(2000–2014)5

Similarly,inPortMoody,thecrimeratedeclinedfromitspeakin2004of5,617propertycrimesper100,000peopleyearoveryear,withjustoneexceptionin2011,until2013resultingina63.6%decreaseoverthattimeperiod(seeFigure4).Aswascommonformostjurisdictions,PortMoodyexperienceda12.5%increaseinitspropertycrimeratein2014comparedtothepreviousyear.Ofnote,ofallthe22jurisdictionsincludedintheseanalyses,onlytheCityofVancouverhaditspeak

5DatacollectedfromStatisticsCanadaCANSIMTable252-0081,June22,2016.

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Burnaby Coquitlam NewWestminster PortCoquitlamPortMoody Richmond UBCVancouver Vancouver

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propertycrimeratein2000.Theiroverallpatternwasalsosomewhatuniquewithadeclineintheirpropertycrimerateeachyearfrom2000to2011,resultingina53.8%decreaseoverthattime,beforeincreasingeachsubsequentyearthrough2014,resultingina9.9%increaseoverthoselastfouryears.

Thefinalpattern,whichwasdemonstratedbyUBCVancouver,NewWestminster,Burnaby,PortCoquitlam,andRichmond,involvedamuchmoreerraticpatternofincreasesanddecreasesyearoveryear(seeFigure4).Forexample,inPortCoquitlam,propertycrimeratesincreasedbetween2000and2003(+35.6percent),decreasedin2004(+12.6percent),increasedin2005(+17.3percent),decreasedbetween2005and2009(-59.5percent),increasedin2010(+8.2percent),heldsteadyin2011beforeincreasingagainin2012(+18.6percent),decreasingin2013(-13.4percent),andfinallyincreasingagainin2014(+13.5percent).ItshouldalsobenotedthatofthejurisdictionsthatcomprisetheGreaterVancouverArea,onlyUBCVancouverexperiencedadeclineintheirpropertycrimeratein2014fromthepreviousyear(-8.4percent).Allotherjurisdictionsinthisareahadanincreaseintheirpropertycrimeratesin2014whencomparedtothepreviousyear.

Insummary,intermsoftheoveralldecreasesinthepropertycrimeratesbetween2000and2014fortheGreaterVancouverArea,thelargestdecreasewasseeninPortMoody(-57.4percent)followedbytheCityofVancouver(-47.9percent),NewWestminster(-47.2percent),Coquitlam(-46.4percent),Burnaby(-46.2percent),UBCVancouver(-39.9percent),Richmond(-35.8percent),andPortCoquitlam(-29.5percent).

Finally,fourmunicipalitiesweregroupedintoacategorydefinedasbeingareasnorthoftheCityofVancouver.ThesecitieswereNorthVancouver,WestVancouver,Squamish,andWhistler.Again,therewasamixedpatternfoundforthesejurisdictions’propertycrimerates(seeFigure5).Forexample,inmorecommonfashion,Whistler,Squamish,andWestVancouverexperiencedanincreaseintheirpropertycrimeratesatthebeginningofthe21stcentury,withapeakbetween2001and2003.However,NorthVancouverCityandNorthVancouverDistrictsawadecreasefrom2000to2001beforetheirpropertycrimeratesbegantoclimbandpeakin2004.Moreover,WestVancouverandNorthVancouverDistrictexperiencedagenerallysmoothdeclinethroughto2011and2013,respectively,beforeseeingsmallincreasesintheirpropertycrimeratesto2014.Infact,WestVancouver’spropertycrimerateincreasedbyonly12.7%from2011to2014,whileNorthVancouverDistrict’spropertycrimerateincreasedbyonly7.8%in2014fromthepreviousyear.

Thepatternofchangewasmuchmoresubstantialfortheotherthreejurisdictions.Forexample,inWhistler,thepropertycrimerateincreasedby12.5%in2001fromthepreviousyearbeforedroppingby23.5%by2005.However,thefollowingyear,thepropertycrimerateincreasedby16.0%beforedroppingyearoveryearthroughto2014,resultingina65.6%decreaseinthepropertycrimerateoverthenexteightyears(seeFigure5).Squamishhadaveryerraticpropertycrimeratebetween2000and2010withratherlargeincreasesanddecreasesovershortperiodsoftime.However,since2010,therehasabeenasteadydecreaseinthepropertycrimeratefrom5,846propertycrimesper100,000peopleto4,285propertycrimesper100,000peoplein2014;adecreaseof26.7%.

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FIGURE5:PROPERTYCRIMERATESFORJURISDICTIONSNORTHOFTHECITYOFVANCOUVER(2000–2014)6

NorthVancouverCityhasseenageneralpatternofafewyearsofincreasingpropertycrimesfollowedbyafewyearsofdecreasingpropertycrime.Ofnotehere,NorthVancouverCityexperienceddecliningpropertycrimeratesfrom2009to2012(-42.2percent)beforeexperiencinganincreasein2013and2014;intotalan8.7%increasebetween2012and2014(seeFigure5).ItisalsoimportanttonotethatbothWhistlerandSquamishsawadecreaseintheircrimeratein2014fromthepreviousyear,whereastheotherthreejurisdictionsfitthemorecommonpatternofpropertycrimerateincreasesin2014.

Intermsoftheoveralldecreasesinthepropertycrimeratesbetween2000and2014forthecitiesnorthoftheCityofVancouver,thelargestdecreasewasseeninWhistler(-65.7percent),followed

6DatacollectedfromStatisticsCanadaCANSIMTable252-0081,June22,2016.

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byNorthVancouverCity(-52.6percent),NorthVancouverDistrict(-46.3percent),Squamish(-41.5percent),andWestVancouver(-37.6percent).

Insummary,forthemostpart,basedonthedataprovidedfromStatisticsCanada,the22jurisdictionsincludedinthisreportexperiencedanincreaseintheirpropertycrimeratesinthefirstfewyearsofthe21stcenturyfollowedbyarelativelysteadyandsubstantialdeclineuntilthelastfewyears.Withveryfewexceptions,mostjurisdictionsexperiencedanincreaseintheirpropertycrimeratesbeginningaround2012,andvirtuallyallofthejurisdictionssawanincreaseintheirpropertycrimeratesin2014comparedto2013.Moreover,basedonthedatapresentedattheSeptember2015MetroVancouverCrimeMeeting,thistrendcontinuedthroughthefirstthreequartersof2015.Basedonthatdata,whiletheoverallpropertycrimeratewasvirtuallythesamein2015asitwasoverthesametimeperiodin2014,everyjurisdiction,withtheexceptionsofDelta,Langley,NewWestminster,NorthVancouver,Richmond,Squamish,Surrey,andWestVancouverexperiencedincreasesintheirpropertycrimerates.ThosejurisdictionswiththelargestincreaseswereMission(+25.6percent),PortMoody(+19.6percent),RidgeMeadows(+16.8percent),Abbotsford(+16.4percent),andCoquitlam(11.2percent).ThejurisdictionswiththelargestdecreaseswereSquamish(-17.3percent),Surrey(-9.9percent),andDelta(-8.6percent).

ThedataofpropertycrimeusedinthisreportwasprovidedbyOSB“E”Divisiononthenumber,type,andlocationofpropertycrimeforeachofthe22jurisdictionsexaminedinthisreportfor2015.Givenpopulationdifferences,itwasexpectedthatpropertycrimewouldnotbeevenlydistributedamongthe22jurisdictionsoftheLowerMainlandDistrictexaminedinthisreport.AsdemonstratedinTable1,nearlyhalfofallthepropertycrimesin2015(47.3percent)wererecordedinjusttwocities,namelySurreyandVancouver.Thiswasnotsurprisinggiventhelargeresidentandambientpopulationsofthesetwocities.7Afterthesetwocities,thelargestnumberofpropertycrimeswasfoundinBurnaby(8.2percent),Richmond(5.7percent),andLangley(5.5percent).Again,ifweconsideronlyrawnumbersofcrimesandnotpopulation,itwasnotsurprisingthatHope,Whistler,Squamish,PortMoody,andWhiteRockhadthefewestreportedincidentsofpropertycrimein2015.

7Aspopulationfiguresfor2015hadnotbeenreleasedbythetimethisreportwaswritten,crimeratescouldnotbeused.

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TABLE1:FREQUENCYOFPROPERTYCRIMESINTHELOWERMAINLANDDISTRICT(2015)

RawNumberofPropertyCrimeOffences

(n=144,293)%ofTotal

CityofVancouver 37,581 26.0%Surrey 30,727 21.3%Burnaby 11,865 8.2%Richmond 8,237 5.7%Langley 7,989 5.5%Abbotsford 6,744 4.7%Chilliwack 6,307 4.4%Coquitlam 5,750 4.0%NorthVancouver 4,599 3.2%MapleRidge 4,506 3.1%NewWestminster 3,493 2.4%Delta 3,279 2.3%PortCoquitlam 2,946 2.0%Mission 2,804 1.9%WestVancouver 1,404 1.0%UBCVancouver 1,111 0.8%PittMeadows 1,001 0.7%WhiteRock 988 0.7%PortMoody 904 0.6%Squamish 753 0.5%Whistler 740 0.5%Hope 565 0.4%

Intermsofthenatureofpropertycrimein2015,Table2presentstheoffencesconsideredforthenextsectionofthereport,therawoccurrencenumberofeachoffencetype,andthepercentageofthetotalthateachoffencetypecontributedtotheoveralltotalofpropertycrimein2015.AsdemonstratedinTable2,one-quarterofallpropertyoffencesin2015intheLMDwasfortheftfromvehicle.Thiswasfollowedbytheftunder$5,000(14.5percent),mischieftoproperty(14.2percent),andshoplifting(10.0percent).Importantly,themoreseriouspropertyoffenceswerelesscommon,suchasbreakandenterofaresidence(6.1percent),arson(0.6percent),andtheftover$5,000(0.6percent).Itisalsointerestingtonotethatdespitetechnologicalsolutions,insurancebenefits,andincreasedpoliceattention,inadditiontospecificpolicestrategies,suchasthebaitcarprogram,autotheftwassixthmostcommonpropertycrimeaccountingfor6.6%ofallpropertycrimein2015.Ineffect,excludingthemoreseriousformsofpropertycrime,suchasautotheft,allformsofbreakandenters,othertheftover$5,000,andarson,78.5%ofpropertycrimein2015intheLMDcouldbecharacterizedasmoreminorinnature.

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TABLE2:NATUREOFPROPERTYCRIMESINTHELOWERMAINLANDDISTRICT(2015)

RawNumber(n=144,293) %ofTotal

TheftFromVehicle 37,158 25.8%OtherTheftUnder$5,000 20,914 14.5%MischieftoProperty 20,467 14.2%Shoplifting 14,359 10.0%Frauds 12,459 8.6%AutoTheft 9,496 6.6%Break&Enter–Residence 8,867 6.1%Break&Enter–Business 7,687 5.3%BikeTheft 6,350 4.4%Break&Enter–Other 2,806 1.9%PossessionofStolenProperty 1,506 1.0%Arson 831 0.6%OtherTheftOver$5,000 909 0.6%

ThereweresomeinterestingdifferencesinhowthefourmostcommonpropertyoffencesweredistributedacrossthevariousjurisdictionsintheLowerMainlandDistrict(Table3).Forexample,withrespecttotheftfromvehicles,Coquitlam(5.2percent)andtheCityofVancouver(27.6percent)wereoverrepresentedintheproportionofthistypeofoffenceintheircities.8Inotherwords,althoughtheCityofVancouverrecorded26.0%ofallthepropertyoffencesin2015amongthe22municipalitiesexamined,itcontributed27.6%ofallthetheftfromvehicleoffences.Ofnote,Surreywassomewhatunderrepresented.For‘othertheftunder$5,000’,onlytheCityofVancouverwasoverrepresented.However,whenconsideringmischieftoproperty,Chilliwack,MapleRidge,andNorthVancouverwereoverrepresented,whiletheCityofVancouverwasunderrepresented.Finally,withrespecttoshoplifting,Burnaby,NewWestminster,theCityofVancouver,andWestVancouverwereoverrepresented,whileSurreywasunderrepresented.Insum,whilethedegreeofoverrepresentedandunderrepresentedwastypicallysmall,itwasinterestingtonotethat,forthetwolargestcities,Vancouverwasoverrepresentedintheftfromvehicle,othertheftunder$5,000,andshoplifting,whilebeingunderrepresentedinmischieftoproperty,whileSurreywasunderrepresentedintheftfromvehicleandmischieftoproperty.

8Cellshighlightedinredrepresentanoverrepresentationofthatspecificoffencetypeforthatmunicipality,whilecellshighlightedinblueindicateanunderrepresentationofthatoffencetypeforthatmunicipality.

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TABLE3:PROPORTIONOFKEYPROPERTYCRIMESBYJURISDICTION(2015)

TheftFromVehicle

(n=37,158)OtherTheftUnder$5,000(n=20,914)

MischiefToProperty(n=20,467)

Shoplifting(n=14,359)

Abbotsford 4.4% 4.0% 5.4% 4.2%Burnaby 8.3% 6.9% 9.1% 11.0%Chilliwack 3.8% 4.5% 5.5% 4.3%Coquitlam 5.2% 3.3% 4.1% 4.0%Delta 2.4% 2.0% 2.9% 1.9%Hope 0.2% 0.5% 0.8% 0.2%Langley 5.0% 5.9% 5.2% 5.9%MapleRidge 3.3% 3.7% 4.3% 2.4%Mission 1.9% 1.9% 2.8% 1.2%NewWestminster 1.9% 2.5% 2.6% 3.7%NorthVancouver 3.2% 2.2% 4.8% 2.8%PittMeadows 0.8% 0.7% 1.0% 0.9%PortCoquitlam 2.7% 1.4% 2.2% 1.7%PortMoody 0.9% 0.6% 0.8% 0.4%Richmond 6.4% 6.3% 4.8% 4.7%Squamish 0.4% 0.6% 0.8% 0.2%Surrey 19.4% 22.3% 20.7% 18.2%UBCVancouver 0.4% 1.1% 0.6% 0.2%CityofVancouver 27.6% 27.5% 19.3% 29.7%WestVancouver 0.8% 0.7% 0.9% 2.2%Whistler 0.2% 1.0% 0.9% 0.2%WhiteRock 0.7% 0.4% 0.8% 0.1%TOTAL 100.0% 100.0% 100.0% 100.0%

Whileeachmunicipality’sspecificpropertycrimeprofilewillbeexaminedingreaterdetailbelow,anotherwaytoconsiderthedataistoexaminethedistributionofeachofthefourmaintypesofpropertycrimeacrosseachofthe22municipalities.Inotherwords,ratherthanthefocusoftheanalysisbeingthecity,thefocusoftheanalysisshiftstothetypeofpropertycrime.AsdemonstratedinTable4,theftfromvehiclesaccountedfor25.8%ofallpropertycrimesin2015;however,manymunicipalitieswereoverrepresentedintheirspecificproportionofpropertycrimesthatweretheftfromvehicles.Forexample,inCoquitlam,one-thirdoftheirpropertycrimewastheftfromvehicle,while27.4%ofDelta’spropertycrimewastheftfromvehicle.Similarly,MapleRidge,PittMeadows,PortCoquitlam,PortMoody,Richmond,andVancouverwereoverrepresentedintheirproportionofpropertycrimethatwastheftfromvehicles.Conversely,manyotherjurisdictionswereunderrepresentedintheproportionoftheirpropertyoffencesthatweretheftforvehicle,suchasWhistler,UBCVancouver,andHope.

Withrespecttotheftunder$5,000,whilethereweremanymunicipalitiesthatwereeitheroverorunderrepresented,therewereonlythreejurisdictionsthatweresubstantiallyoverrepresented;namely,Whistler(27.4percent),UBCVancouver(21.2percent),andHope(19.3percent).Similarly,therewerefourmunicipalitiesthatweresubstantiallyunderrepresentedintheirproportionoftheftunder$5,000;namely,NorthVancouver(10.2percent),PortCoquitlam(9.9percent),WestVancouver(10.8percent),andWhiteRock(9.1percent).

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Manymunicipalitieswereoverrepresentedintheirproportionofpropertycrimesthatweremischieftoproperty;however,thosewiththelargestoverrepresentationincludedHope(27.4percent),Mission(20.2percent),NorthVancouver(21.5percent),Squamish(20.5percent),andWhistler(24.7percent).Afewmunicipalitieswereunderrepresentedintheirproportionofmischieftoproperty;namely,Richmond,UBCVancouver,andVancouver.Finally,whenitcametoshoplifting,mostmunicipalitieswereunderrepresented;however,Burnaby,NewWestminster,PittMeadows,Vancouver,andWestVancouverwereoverrepresented.

TABLE4:DISTRIBUTIONOFTHEFOURMOSTCOMMONPROPERTYCRIMESWITHINEACHJURISDICTION(2015)

TheftFromVehicle OtherTheftUnder

$5,000MischiefToProperty Shoplifting

Abbotsford 24.2% 12.3% 16.4% 8.8%Burnaby 26.0% 12.2% 15.7% 13.3%Chilliwack 22.6% 15.0% 17.9% 9.9%Coquitlam 33.4% 12.1% 14.6% 10.0%Delta 27.4% 12.7% 17.9% 8.5%Hope 15.8% 19.3% 27.4% 3.9%Langley 23.2% 15.6% 13.4% 10.5%MapleRidge 27.4% 17.0% 19.5% 7.5%Mission 25.7% 13.8% 20.2% 6.4%NewWestminster 20.1% 14.8% 15.2% 15.3%NorthVancouver 25.9% 10.2% 21.5% 8.7%PittMeadows 28.1% 14.7% 19.5% 13.6%PortCoquitlam 33.9% 9.9% 15.4% 8.2%PortMoody 35.2% 12.8% 17.9% 6.6%Richmond 28.7% 15.9% 11.8% 8.1%Squamish 20.1% 15.8% 20.5% 4.0%Surrey 23.5% 15.2% 13.8% 8.5%UBCVancouver 14.5% 21.2% 10.7% 2.4%CityofVancouver 27.3% 15.3% 10.5% 11.3%WestVancouver 21.9% 10.8% 13.5% 22.4%Whistler 11.5% 27.4% 24.7% 3.0%WhiteRock 25.4% 9.1% 15.6% 1.6%TOTAL 25.8% 14.5% 14.2% 10.0%

Whilethecircumstanceofeachpropertyoffencewasnotexamined,giventhefindingspresentedinTables2and4,nearlytwo-thirds(64.5percent)ofallpropertycrimesin2015weretheftfromvehicles,theftunder$5,000,mischieftoproperty,orshoplifting.Ofnote,theseparticularcrimesfitwellintotwowellestablishedcriminologicaltheoriesofcrime;routineactivitiestheoryandsocialdisorganizationtheory.Giventhis,thenextsectionofthisreportwillexamineseveralleadingcontemporarytheoriesdesignedtoexplainpropertycrimeandconsiderwhattheresearchliteraturesaysabouttherelativecontributionofvarioussocio-economic,socio-demographic,andjurisdictioncompositionfactorsonpropertycrimerates.

Followingthetheoreticalexplanations,theactualdistributionofpropertycrimein2015ineachjurisdictionwillbepresentedandexaminedtodeterminewhethertherearepropertycrime‘hot

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spots’ineachjurisdiction.Oncethespatialdistributionofpropertycrimeineachjurisdictionispresented,censustractdatawillbeusedtoexplorethesocio-demographicandsocio-economicfeaturesofthesehotspotstoassesswhetherthereareanyuniquefeaturesinthesehotspotsthatcouldexplaintheincreaseinpropertycrimeratesinthosejurisdictionsthathaveexperiencedrecentincreases.Together,thetheoreticalexplanationsforvariationsinpropertycrimealongwiththeempiricalexaminationofthesevariationswillbeusedtoformulateseveralrecommendationsforpolicetoconsider.

SocialTheoriesExplainingPropertyCrimeSOCIALDISORGANIZATION

Thestudyofgeographicclusteringofcrimewaspopularintheearlytomid-1900sintheUnitedStates,duemainlytoalargenumberofempiricalresearchstudiescarriedoutbysociologistsattheUniversityofChicago.Arguablyoneofthemostinfluentialtheories,whichisstillusedtodaytoexplainpropertycrime,issocialdisorganizationtheory,developedbyShawandMcKay(1942).Oneofthekeyassumptionsofsocialdisorganizationtheoryisthathumanbehaviorisshapedbytheenvironment.Thisdoesnotmeanthatbiologicalorindividualfactorsareignoredbysocialdisorganizationtheorists;itsimplyassumesthattheenvironmentinwhichanindividuallives,aswellasothersocialfactors,isofgreaterimportanceindeterminingandexplainingbehaviour(Heidt&Wheeldon,2015).Inparticular,ofkeyimportancetosocialdisorganizationistheneighborhoodanindividuallivesin,andtheeffectsthatneighborhoodcharacteristicscanhaveoninfluencingone’sbehavior.

ShawandMcKaywereheavilyinfluencedbythesociologicalworksofauthorslikeBurgess(1925)andhisconcentriczonetheory,whicharguedthatcrimewasnotevenlydistributedthroughoutacity.Instead,Burgess(1925)demonstratedthatrapidpopulationchangesinanurbanenvironmentledtocertain(inner)partsofthecitybecomingmorepronetocrimeproblems,whileother(suburban)areasenjoyedmuchlowercrimerates,withamajordrivingfactorbeingthetransientnatureofinnercityneighbourhoods.Burgess(1925)arguedthatthecenterorcoreofacity,generallyfilledwithcommercialorindustrialbusinesses,stores,offices,restaurants,andentertainment,wasoftensurroundedbyanotherzone,knownasazone-in-transition.Thiszone-in-transition,ofgreatinteresttocriminologistsduetotheoftenhighcrimeratesinthiszine,generallycontainedslumsorunderdevelopedareas,andtendedtobethelocationthatfirst-generationimmigrantsmovedtouponarrivingtoanewcountry,simplyduetothelowrentsthatwereavailable.Thiszone-in-transitionwasofteninflux,characterizedbyhighresidentialmobility,peoplewithlowerlevelsofeducation,andpeopleoflowersocio-economicstatus.Inaddition,thiszonewasconstantlybeinginvadedbyurbansprawlasthecenterofthecitygrewoutwards.Thisconstantpopulationchurnpreventedasenseofcommunityorstrongrelationshipsbetweenpeoplelivinginthezone-in-transition.Thezone-in-transitionalsotendedtobefilledwithalargenumberofdifferentracialgroupsandethnicitiesthatlackedmanytangibleconnections,eitherduetolanguage,cultural,orreligiousdifferences.Ineffect,thiszonesufferedfromlowlevelsofsocialcapitalandlowlevelsofcollectiveefficacy.Burgess(1925)notedthatallofthesefeaturescontributedtoaconstantstateofsocialdisorganizationandlowlevelsofsocialcontrol,which

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resultedinhigherratesofcrimeanddelinquency.Burgess(1925)referredtothenextarea,Zone3,astheareaofworkingmen’shomes,ofteninhabitedbyindividualsworkinginthecitycentre.Often,asthoselivinginthezone-in-transitionbecamemoresuccessful,oftenafteroneortwogenerations,residentswouldeventuallymovetoliveinZone3,asitwasmorestable,safer,anddesirable.Thisarea,alongwiththenextzone,tendedtohavemuchlowerlevelsofresidentialmobilitycomparedtothezone-in-transition.Zone4,whichBurgess(1925)referredtoastheresidentialzone,wasgenerallyfilledwithmoresuccessfulsinglefamilydwellings,andupperandmiddleclassapartmentbuildings.Finally,theouterareaofacity,Zone5,wasknownasthecommuterzone,whichincludedthesuburbsofthelargercity,orsmallersatellitecities,often30to60minutesawayfromthecitycore.Zones3,4and5tendedtohavefarlowerratesofcrimeanddelinquencythanthezone-in-transition.

Basedonthesefindings,ShawandMcKaypositedthatneighborhoodorganizationwaslikelyakeyfactorindeterminingwhetheranindividualwouldbecomeinvolvedincrimeandalsothelevelofcrimeinaspecificpartofthecity(Lilly,Cullen,&Ball,2007).Insupportofthis,theirresearchonjuvenilecrimesuggestedthatcrimetendedtohavehigherconcentrationsinspecificareas,whileothersmaintainedlowercrimerates,evenwhencontrollingforpopulationgrowth.ThesefindingsledShawandMcKay(1942)toconcludethatconcentrationsofcrimewithinacitywerenotduesimplytopopulationgrowth,butwerelikelyduetoothersocialfactorswithinthosespecificcommunitiesorneighbourhoods.Inotherwords,itwassomethingabouttheenvironment,ratherthanthespecificcharacteristicsofthepeoplelivingtherethatcontributedtoincreasedcrimeratesincertainpartsofacity.

Ineffect,socialdisorganizationtheorylinksthecharacteristicsofaneighborhoodorcommunitytocrimerates,andpositsthatacommunitywouldbecomedisruptedordisorganizedbyseveralkeyfactors,suchasrapidpopulationgrowth,immigration,oraninvasionofbusinessorindustryintoaresidentialarea.Asthisoccurred,theinternalnormsandstandardsofthecommunitybegintoweaken,breakdown,andeventuallydisappear(Bruinsma,Pauwels,Weerman,&Bernasco,2013).Asthesenormsbreakdown,aneighborhoodwouldbeunabletoexertsocialcontroloverthebehaviouroftheindividualslivingthere,whichcouldleadtohigherratesofdelinquencyandcrime.

ShawandMcKay(1942)arguedthatsocialdisorganizationwastheoutcomeofthreemaincharacteristics,namelyloweconomicstatus(poverty),culturalheterogeneity,includingindividualsfrommultipleethnicorreligiousbackgrounds,andhighlevelsofresidentialmobility.Loweconomicstatuscouldbeindicatedbyhigherratesofsocialassistance,lowerratesofhomeownership,andlowerjobwagesforindividualsinthecommunity.Withregardstoculturalheterogeneity,neighborhoodswithmanysmallgroupsofdifferentethnicity,religious,culture,languages,andnormswouldexperiencehighlevelsofsocialdisorganization.Itwasarguedthatthesevariousgroupswouldhavedifficultyfindingcommonground,andwouldhaveahardtimecommunicatingwithoneanotherduetolanguageandculturalbarriers,leadingtoweakornon-existentpersonalrelationships.ShawandMcKay(1942)alsobelievedthatindividualslivinginthesecommunitiesofloweconomicstatuswouldbecomefrustratedwhenconfrontedwithindividualsofhigheconomicstatus,whichcouldalsoleadtofurthercriminalbehavior.Theyarguedthatasthefrequencyofthesecharacteristicsincreased,thecommunitywouldhavealoweredresistancetounconventionalbehavioralnormschallengingtheconventionalnormsandmoral

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values.Asdifferentgroupswithdifferentsetsofnormsandvaluesmovedintoadisorganizedarea,itwouldbecomefurtherdisorganized.Residentialmobility,partiallylinkedtolowerratesofhomeownership,wouldleadtoresidentsconstantlymovinginoroutoftheneighborhood,makingitdifficultforindividualstocreatestrongfriendshipnetworks.Theconstantchangeinresidentscouldalsoleadtoinstitutions,suchasschoolsorchurches,havingweakornon-existentsocialcontrol.Sampson(1986)lateraddedtheadditionalfactoroffamilydisruptiontosocialdisorganizationtheory,statingthatmaritalproblems,suchasdivorce,wouldlikelyweakentheinformalsocialcontrolofyouth,whichcouldleadtohighercrimerates.

Althoughsocialdisorganizationtheoryfelloutoffavorduringthe1960sand1970saftermethodologicalissueswithShawandMcKay’searlyworkswerepointedout(Bursik,1988;Weisburd,Bruinsma,&Bernasco,2009),thistheoreticalframeworkhasseenaresurgenceininterestsincethe1980s,withelaborationsontheoriginalmodel,aswellasnewextensionslikeBursikandGrasmick’scommunitycontroltheory(1993)andSampson’scollectiveefficacytheory(1997).

BursikandGrasmick(1993)identifiedseverallevelsofcommunitycontrolintheirtheory.Thefirstlevelofcontrol,privatecontrol,wascenteredonpersonalrelationshipsandfriendshipswithotherindividualsinthecommunity,whichenforcednormsinformally.Forexample,ifanindividual’sbehaviordidnotconformtothesocialnorm,friendshipmightbewithdrawn.Thesecondlevelofcontrolwasidentifiedasparochialcontrol,andreferredtothecontrolexertedbyinstitutions,suchasschoolsandchurches.Thesefirsttwolevelsofcommunitycontrol,whileinformal,allowedindividualstointegrateandconformtothenormsofacommunity(Heidt&Wheeldon,2015).ThethirdlevelofcontrolidentifiedbyBursikandGrasmick(1993)wasthatofpubliccontrol,whichfocusedontheabilityoftheneighborhoodtosecureresourcesfrompublicandprivateagenciesoutsideoftheneighborhood,suchasfederalgovernmentagencies.Theseresourcescouldincludeeconomicresourcesforthingslikeschools,recreationcentres,orlawenforcement.BursikandGrasmick(1993)arguedthataneighborhoodthatwaseconomicallydeprived,andwasunabletosecurethesetypesofoutsideresources,wouldlikelysufferfromhighercrimerates.Theyalsopositedthatanareawithhighlevelsofpoverty,butlowcrimerates,couldexist,aslongastheywereabletosecureassistancefromoutsideagencies.Thiswouldoccurbecausewell-fundedpublicinstitutions,suchasschools,wouldbeabletoexertcontrolintheneighborhood,whileunderfundedinstitutionswouldnot.

Recentresearchonsocialdisorganizationhasbeenlargelysupportive,particularlyfortheelementsofloweconomicstatus,familydisruption,weaksocialnetworks,highresidentialmobility,andlowcommunityorganization,whichhaveallbeenassociatedtohighercrimerates-particularlyinurbanareas(Miethe,Hughes,&McDowall1991;Sampson&Groves,1989;Lowenkamp,Cullen,&Pratt,2003;Hipp,2007;Bellair&Browning,2010;Kaylen&Pridemore,2013).Thatbeingsaid,someauthorshavequestionedtheexplanatoryabilityofsocialdisorganizationtheoryinruralareasduetothequalityofpolicecrimereportdataintheseareas,andsomeinconsistentresultsfromempiricalresearchinthesesettings(Wiersmaetal.,2000;Kaylen&Pridemore,2013).Researchoncommunitycontroltheory,andtheabilityoforganizationstocontributetosocialorder,ismorescarce,buttheresearchavailableislargelysupportive(Triplett,Gainey,&Sun,2003;Maeres&Korkran,2007;Slocum,Rengifo,Choi,&Herrmann,2013).Whilesomecommunityinstitutions

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producefewcrime-reducingeffects,othersareassociatedwithnotabledecreasesincrime.Forexample,organizationsthataimtoimprovethewell-beingoffamiliesandchildren,suchasschools,activitycenters,orserviceproviders,tendtohaveapositiveeffectonreducingpropertycrime.

ROUTINEACTIVITYTHEORY

Ratherthanfocusingonsocialfactorswithinaneighborhood,CohenandFelson(1979)focusedonthespecificcircumstancesthatledtoanoffendercommittingacriminaloffence.Theirtheory,entitledroutineactivitytheory,isstronglyrootedinthebeliefthatoffendersmakearational,logicaldecisiontocommitacrimeinanattempttogainsomebenefitorpleasure.Insteadoffocusingonexternalfactors,suchasneighborhoodcomposition,routineactivitytheoryfocusesontheindividual,althoughitdoesnotfocusonindividual-levelcharacteristics.Routineactivitytheorydoesnotpositthatpeopleareimmunetotheeffectsoftheirenvironment,andadmitsthatsometimeshumanbehaviorisnotcompletelyrationalorlogical,butholdsthebeliefthatpeoplehavefreewilltocommitornotcommitcrimeand,therefore,makeaconsciouschoicetocommitanoffence(Heidt&Wheeldon,2015).

ThreemainprincipleswerecentraltoCohenandFelson’s(1979)routineactivitytheory.Thefirstwasthat,likemostpeople,offendersareinterestedingainingquick,easypleasure,whiletypicallyattemptingtoavoidimminentpainorpunishment.Next,CohenandFelson(1979)believedthattheday-to-dayactivitiesinanindividual’slife,describedas‘routineactivities’,wouldsetthestageforillegalorcriminalchoicesbyanindividual.Finally,theyarguedthatcriminalopportunitiesandcrimeratescouldbeaffectedbyalteringdailyroutines.Morespecifically,CohenandFelson(1979)positedthatcrimewouldoccurwhentherewasaconvergenceintimeandspacebetweenamotivatedorlikelyoffender,asuitabletarget,andtheabsenceofcapableguardianship.

Whilemanycriminologistshavefocusedonwhatmakesanddifferentiatesalikelyoffender,routineactivitytheorybelievedthatincreasingcrimeratesweremorecloselyassociatedtoandtheresultofchangesintheothertwofactors,namelyasuitabletargetandtheabsenceofacapableguardian.CohenandFelson(1979)notedthat,whiletheories,suchassocialdisorganization,focusedonsocialissues,likepoverty,asacauseofcrime,empiricalevidenceshowedthatpovertyactuallydecreasedintheUnitedStatesafterWorldWarII.Theoretically,thisshouldhaveresultedinadecreaseinthecrimerateoverthesameperiodoftime;however,crimeratescontinuedtoincreasethroughoutthe1950sand1960s.ThisledCohenandFelson(1979)topositthattheincreasedcrimeratewasduetochangesinday-to-dayactivitiesorthe‘routineactivities’ofpeople.OfparticularinteresttoCohenandFelsonwastheincreasedleisuretimespentawayfromthehomebymanypeople,aswellastheincreasednumberofwomenenteringtheworkforceandspendingtimeawayfromtheirhomes.ForCohenandFelson,thishadtwoimportant,unintendedconsequencesthatincreasedtheopportunityforcrime.First,homeswereleftwithoutcapableguardianshipfarmoreoftenthaneverbefore,and,second,householdshadmorediscretionarymoneytospendonmaterialgoodsthatwouldattractpropertyoffenders.

CohenandFelson(1979)showedthat,asmorewomenenteredtheworkforce,leadingtohigherlevelsofhouseholdswithoutacapableguardian,theratesofrape,robbery,assault,andtheftincreased.Ayearlater,in1980,Cohen,Felson,andLandusedroutineactivitytheorytoexplainand

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predictpropertycrimeratesintheUnitedStates,showingthatpropertycrimedecreasedinhighdensityresidentialareasdue,theybelieved,tohigherratesofguardianship.Otherstudieshavedemonstratedthatvariationsinthepatternsofindividualbehaviorhashadaneffectoncrimebychangingthelikelihoodthatamotivatedoffenderwillcomeintocontactwithasuitabletargetintheabsenceofacapableguardian(McNeely,2015).

Oneofthemostprominenttheoriesstemmingfromroutineactivitytheoryislifestyleexposuretheory,developedbyHindenlang,Gottfredson,andGarofalo(1978),whichfocusedonindividualvictimization.Whileroutineactivitytheorylargelyfocusedonmacrolevelexplanationsforcrime,lifestyleexposuretheoryfocusedonexplainingindividuallevelvictimization.Hindenlangetal.(1978)believedthatdifferentdemographicgroupssufferedfromvictimizationatdifferentratesbecauseoftheirdifferencesin‘lifestyle’.Lifestyle,asdefinedbyHindenlangetal.(1978),includedvariouselementsofroutinedailyactivity,includingschool,work,andleisureactivities,andpositedthatdemographiccharacteristics,suchasage,sex,race,income,oreducation,wouldallhaveaneffectonwhatdailyactivitiesanindividualwouldengagein.Asanindividualwasplacedintohigh-riskplaces,particularlyinlocationswithmotivatedoffenders,theirlikelihoodofbeingavictimofcrimewouldincrease.Cohen,Kluegel,andLand(1981)furtherexpandedonthistheorybystatingthatfivefactorswouldaffectthelikelihoodofcriminalvictimization;exposure,proximity,attractiveness,guardianship,andthepropertiesofthecrimethemselves.Cohenetal.(1981)believedthatindividualsorobjectsthatweremorevisibletomotivatedoffenderswouldbemorelikelytobevictimized.Forexample,individualsthatspendmoretimeawayfromtheirhomeswereatgreaterriskforvictimization,notbecausetheyweredoinganythingwrong,butsimplybeleavingtheirhomesunprotectedandbybeinginlocationswheregroupsofpeoplewhomaynotknoweachothermix.Second,proximityreferredtothedistancebetweenamotivatedoffenderandapotentialtarget.Allthingsbeingequal,itwasarguedthatindividualsclosertoamotivatedoffenderweremorelikelytobevictimized.Forexample,individualslivinginahigh-crimeneighborhoodhadamuchhigherchanceofbeingatargetofcrimeduetotheirconstantcloseproximitytomotivatedoffenders.Third,Cohenetal.(1981)positedthatvictimsortargetsthatwereseenasattractiveordesirable,whetherduetothefinancialgainorthepotentialeasewithwhichthetargetcouldbeoffendedagainst,wouldleadtohigherratesofvictimization.Thishasbeenparticularlytrueforeconomiccrimes,liketheftorburglary(McNeeley,2015).Fourth,guardianshipwasdefinedasanysecuritymeasureaimedatdecreasingvictimization,suchaspeopleorobjectscapableofpreventingcrime.Finally,Cohenetal.(1981)arguedthatopportunitycouldlargelyvarybythetypeofcrimeitself.Specifically,crimes,suchasburglaryortheft,couldbeexplainedbytargetattractiveness,guardianship,exposure,andproximitytoamotivatedoffender.

Thereisasubstantialamountofempiricalevidenceshowingthatbothpropertyandviolentvictimizationincreaseswithexposure,asoutlinedbyMcNeely(2015).Researchhasconsistentlyfoundthatvictimizationisfarmorelikelywhentheproximitytomotivatedoffendersishigher,particularlyforcrimessuchasburglary,theft,andassault.Theimportanceofattractivetargetshasreceivedsubstantialsupportinacademicliterature,particularlyforeconomiccrimes(McNeely,2015).Forexample,MietheandMeier(1990)showedthathomeswithexpensiveitems,suchashouseholdelectronics,weremorelikelytobeburglarized,andindividualswhocarriedcashmorefrequentlywereatanincreasedriskforbeingthevictimofarobberyandanassault.Increasingguardianship,eitherthroughmethodsliketargethardening(alarms,barsonawindow),or

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individualscapableofpreventingcrime(suchassecurityguards)hasbeenshowntohaveastrongnegativerelationshipwithbothpropertyandviolentcrime(McNeely,2015).Forexample,researchhasshownthatsimplylockingone’sdoors,owningadog,orhavinganeighborwatchtheirhomesdecreasesthelikelihoodofbeingthevictimofaburglary(Miethe&McDowall,1993;Wilcox,Land,&Miethe,1994).Tacticssuchastheseunderliethenextperspectivecommonlyusedtoexplainandreducetheoccurrenceofpropertycrime,CrimePreventionthroughEnvironmentalDesign.

CRIMEPREVENTIONTHROUGHENVIRONMENTALDESIGN(CPTED)

Crimepreventionthroughenvironmentaldesign,orCPTED,focusesontherelationshipbetweenindividualfactorsandthephysicalenvironment.Inparticular,CPTEDpositsthatthephysicalenvironmentcanplayasignificantroleindetermininganindividual’sbehaviour(Jacobs,1961;Jeffery,1971),andifproperlydesigned,canreducetheoccurrenceofcrime(Sohn,2016).Jeffery(1971)believedthatarchitecture,lighting,andurbanplanningcouldplayasignificantroleineitherreducingorincreasingcriminalactivity;awell-litarea,forexample,wouldlikelybesaferthanadarkalleyway,andanopen,highlyvisibleareawouldbesaferthanaclosed-offareawitharchitectureblockinglinesofsight.Jacobsstatedthatforastreettobesafe,it“musthavethreemainqualities.Theremustbeacleardemarcationbetweenwhatpublicspaceisandwhatprivatespaceis.Theremustbeeyesuponthestreet;eyesbelongingtothosewemightcallnaturalproprietorsofthestreet.Thebuildingonastreetequippedtohandlestrangers…mustbeorientedtothestreet.Thesidewalkmusthaveusersonitfairlycontinuously,bothtoaddtothenumberofeffectiveeyesonthestreetandtointroducepeopleinbuildingsalongthestreettowatchthesidewalksinsufficientnumbers”(1961:31).

MuchoftheresearchonCPTEDfocusesonthefourmainprinciplesofterritory,naturalsurveillance,activitysupport,andaccesscontrol(Cozens&Love,2015;Sohn,2016).Theprincipleofterritoryfocusesonurbandesignthatclearlydelineatesprivatespaceandpublicspace,alongwiththebeliefthatpeoplewillprotecttheirownprivatespace,andwillrespecttheprivatespaceofothers.ResearchbyBrownandAltman(1983)showedthatapplyingconceptsofterritorialityreducedtheratesofburglaryinresidentialareasbyaffectingtheevaluationofatargetbypotentialoffenders.Naturalsurveillancereferstotheuseoflight,windows,doorlocations,andlandscapingtoimprovevisibilityandincreasethelikelihoodofspottingoffendersinthearea.Forexample,removingshelvesandpostersblockingthewindowsofabusinesstoimprovevisibilityfromandtotheoutsidecouldreducethechancesofarobbery,whileimprovingoutdoorlightingandtrimmingbushesandhedgesmightimprovesafetyinapublicpark.Improvingsurveillanceandlightinginanareahasalsobeenshowntoimproveneighborhoodsafety(WelshandFarrington,2002).Activitysupportfocusesonthepromotionofsafepublicspacesforoutdooractivities,mainlythroughpublicplanningattheneighborhoodlevel.Forexample,improvingsidewalksandlightingalongpubliccorridors,supportingpublicactivitiesinparksandlargepublicspaces,andimprovingpedestrianmovementinaneighborhoodhaveallbeenlinkedtoreducingcrime(Sohn,2016).Finally,thelastprincipleofCPTEDisthatofaccesscontrol.Accesscontrolattemptstoreducecrimebydenyingoffendersaccesstoareaswithpotentialtargetsforcrime.Italsoattemptstoincreasethesenseofrisktopotentialoffendersinanareainordertodeterpotentialoffenders.Accesscontrolcanoftenincludetargethardeningmethods,suchasbarsonawindow,highfences,oralarmsystems.Ata

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neighborhoodlevel,itcouldincludelimitingthroughtraffic,limitingparking,orcreatingotherbarriersorrestrictions.Previousresearchhasshownthesemethodstobeeffectiveinreducingcrime(Yang,2006;Armitage,2010).

Sinceitsemergence,anumberofauthorshavecontributedtothedevelopmentandimprovementofCPTED.Forexample,environmentalcriminology,developedbyBrantinghamandBrantingham(1981),BrokenWindowstheory,developedbyWilsonandKelling(1982),andsituationalcrimeprevention(Clarke,1997,CornishandClarke,2003)areallexamplesoftheoriesbuildingontheideasofCPTED.Further,CPTEDtheoriesaresupportedbyanumberofgovernmentsaroundtheworld,includingtheUnitedStates,Canada,Australia,andtheUnitedKingdom.Thatbeingsaid,muchoftheempiricalresearchonCPTED,andthenumeroustheoriesdevelopedsincetheemergenceofCPTED,arebasedonindividualcasestudies,andaresomewhatlimitedintheirscope(Cozens&Love,2015).However,manyofthosestudiesfocusingonproperty-relatedoffencesshowstrongevidenceofthepositiveeffectsincreasedsecurityhashadonreducingcrimerates(Farrell,Tilley,Tseloni,&Mailey2008;Farrell,Tseloni,Mailey&Tilley,2011;Bassmann,2011).Forexample,theinstallationanduseofimmobilizersinautomobileshashadasignificantpositiveeffectonreducingcartheftintheUnitedStates(FujitaandMaxfield,2012),theUnitedKingdom(ClancyandLulham,2014),andAustralia(Mayhew,2012)simplybyreducingthenumberofsuitabletargetsavailablefortheft.

Socio-DemographicFactorsofPropertyCrimeWhilesocio-demographicfeaturesofaneighborhood,suchaspopulationdensity,residentialmobility,andgenderandagedistributionshaveoftenbeenafocusofstudywhenattemptingtoexplaincrimeratesoverthepastseveraldecades,itisbecomingapparentinmorerecentliteraturethattherearesubstantialmethodologicalchallengeswiththisprocess.Inparticular,pastresearchhasfocusedonthedemographicfeaturesoflargeareas,suchasacity,orevenastate,andhastriedtolinkthesemacro-leveldemographicfeaturestocrimerates.Itisbecomingmoreandmoreapparentthatthesetypesofmacro-levelanalysesarenotterriblyaccurateinexplainingcrime.Instead,morecontemporaryliteraturehasshiftedtofocusingonmicro-levelsofanalysis.Ratherthanlookingbroadlyatanentirecity,researchersarestartingtonarrowtheirfocustoafewblocks,asinglestreet,orevenasinglestreetcornerinanattempttomoreaccuratelyexplaincrime(BoessenandHipp,2015).

POPULATIONSIZEANDDENSITY

Populationdensity,oftendefinedasthenumberofpeoplelivinginonesquarekilometerinCanada,isalsosometimesdefinedbythenumberofpeoplelivinginadwelling,orthenumberofpeopleperroominadwelling(Harries,2006).Muchoftheresearchlookingattherelationshipbetweencrimeandpopulationdensityfocusesonaparticulartypeofoffence,suchasmurderorsomeotherviolentcrime,drugcrimes,orpropertycrime.Theresultsofthesereportscanvarygreatly,withsomeseeinganassociation,whileothersfindnorelationship;however,themajorityofreportstend

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tosuggestthatmosttypesofcrimesappeartoincreasewhenpopulationdensityincreases(Ackerman,1998;Harries,2006).

Whilepopulationsizeanddensitywithinacityhasoftenbeennotedashavinganeffectoncrimerates,particularlyviolentcrimes,justhowsubstantialthatrelationshipishasbeendebatedintheresearchliteraturefordecades(Harries,2006).Infact,therelationshipbetweenpopulationandcrimeisnotassimpleasitseems,andtheresultsfromempiricalresearchhavebeenmixed.Thiscouldbedue,inlargepart,tothemethodologicalchallengesindeterminingtherelationshipbetweencrimeandpopulation,suchastheissueofclearlyidentifyingtheboundariesofacityoraparticularurbanarea.Forexample,theremaybeseveralsmaller‘cities’inacontiguousurbanarea,oramixofregions,municipalities,orboroughs.Crimeinthesedistrictscanbedifficulttoseparatefromonecitytoanother,particularlycross-jurisdictionalcrimeorwhentryingtoaccountforindividualslivinginonecitywhileworkingortravellinginanother.Forinstance,someauthorshavepointedouttheproblemofcrime‘spill-over’,whereoffendersfromalargercitywillcommitcrimesinsmallerneighbouringcommunities(Ackerman,1998).Furthercomplicatingtheissue,thesocio-economicstatusofaneighborhoodcanalsohaveasignificanteffectontheamountandtypeofcrimeanareaexperiences(Harries,2006;Hipp&Roussell,2013).Forexample,aclusterofhighdensity,butveryaffluenthomescouldseenodifferenceinaveragecrimerates,whileapoorer,highdensityareamightseeanincrease.HippandRoussell(2013)triedtosolvethisissuebylookingatmicrodensityandmacrodensity,andfoundsupportforthetheorythatcrimeratesincreasewithdensityatthemacrolevelforcrimeslikerobberyandtheft,albeitinanon-linearfashion.

Whiletheresearchliteraturehasshownthatpopulationdensitycanhavevaryingeffectsondifferenttypesofcrimes,theresultsfromempiricalresearchissomewhatmixed.Forexample,theresultsontheeffectofpopulationdensitycanchangedependingontheproximityofthejurisdictiontoothermajorcitiesorthesocio-economicstatusoftheneighborhood.Thatbeingsaid,thereseemstobeatleastsomesupportfortheideathatpropertycrimes,suchasrobberyandtheft,increasewithpopulationdensity(Hipp&Roussell,2013).

RESIDENTIALMOBILITY

Therelationshipbetweencrimeandresidentialmobilityhaslongbeenatopicofdiscussionforsociologistsandcriminologists.Numeroussociologists,asdiscussedpreviouslywithsocialdisorganizationtheory,pointedoutthathighlevelsofresidentialmobility,oftenlinkedtolowlevelsofhomeownership,couldleadtocrimeduetoabreakdownofinterpersonalrelationshipsandconnectionstosocialinstitutionsinthecommunity.This,inturn,couldimpedesocialcontrolwithinaneighborhoodandreducethewillingnessofaneighbourtointerveneonthebehalfofanotherresident,thuscontributingtohighercrimerates.Researchappearstosupportthistheorybyshowingthathighlevelsofresidentialmobilityisoftenrelatedtohigherratesofcrime,particularlyvarioustypesofpropertycrime,suchasrobbery,burglary,motorvehicletheft,andlarceny(Boessen&Hipp,2015).Thistrendisespeciallytrueforadolescents,whoexhibithigherratesofcriminalbehavior,particularlyminoroffencesanddrugoffences,whencomparedtopeerswhodonothaveahighlevelofresidentialmobility(Porter&Vogel,2013).Thatbeingsaid,PorterandVogel(2013)alsostressedtheimportanceofindividual,family,andneighborhoodfactorsthat

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neededtobeaccountedforwhenattemptingtomakethelinkbetweenresidentialmobilityandcrime.

Interestingly,crimeratescanoftendriveincreasedresidentialmobility,whereindividualsseektoleaveaneighborhoodbecauseofitsrealorimaginedhighcrimerate(Hipp,Tita,&Greenbaum,2009).Astheareabecomeslessdesirable,andasmorepeopleleavethearea,homevaluesoftendecrease,leadingtoaconcentrationofpovertyand,alongwithit,higherratesofcrime(Tita,Petras,&Greenbaum,2006).Furthercomplicatingtheproblem,ifthepeoplemovingintotheneighborhooddifferinethnicityfromthecurrentresidents,highercrimeratescouldoccurduetoincreasedethnicheterogeneity(Hipp,Tita,&Greenbaum,2009).ThiscreateswhatHipp,Tita,andGreenbaum(2009)describedasaself-perpetuatingcycleorfeedbackeffectofcrimeinaneighborhood.

Ineffect,theresearchliteraturelargelysupportstheideathathighlevelsofresidentialmobility,orpeoplefrequentlymovinginoroutofaneighborhood,cancauseanincreaseincrimerates,particularlypropertycrimerates,suchastheft,robbery,burglary,andmotorvehicletheft(Boessen&Hipp,2015).Accordingtotheliterature,itwouldappearthatresidentialmobilityhasameaningfuleffectonyouthandadolescentsinparticular,whooftenexhibithigherratesofcriminalbehaviorwhenexperiencinghigherlevelsofresidentialmobility.Thisincreaseincrimecanhavemanynegativeoutcomesforacommunity,andcanoftencauseaneighborhoodtobecomeundesirableforresidentialrentersorbuyers,leadingtodecreasedhomeandpropertyvalues,which,inturn,cancontributetohigherlevelsofpovertyandhigherlevelsofcrime.

THENUMBERANDDENSITYOFPOLICE

Therearefewjobsthatundertakealargervarietyoftasksthanapoliceofficer.Inadditiontorespondingtocallsforservicefromthepublic,policealsoserveasfirstrespondersinemergenciesandaccidents,undertakepatroldutiesinneighborhoodstolookoutforcrime,actascaretakersforthecityandcommunity,andoftenserveasmediatorsinnon-criminaldisputesbetweenresidentsandstrangers.Itshouldbenosurprisethenthatthenumberanddensityofpoliceofficersinacityisoftenanareaoffocusforresearcherstryingtoexplaincrimerates.Policeofficertasksoftenfallintooneoftwocategories;reactivepolicing,suchasrespondingto9-11calls,orproactivepolicing,suchassettinguparoadblocktosearchforimpaireddriversorpatrollinganeighborhoodhotspot.Obviously,whenpoliceofficersspendthemajorityoftheirtimeservingintheirreactivecapacity,itleaveslittleornotimeforproactivework,suchasfocusingonproblemareasorchronic,prolific,orpriorityoffenders.Thiscanbeasignificantproblemforpolicingagencies,asresearchhasshownthatfocusingonthesetypesofoffendersandspecificpublicsafetyissuesisakeystrategyinreducingcrime(Cohen,Plecas,McCormick,&Peters2014).

Thatbeingsaid,gaugingindividualpoliceofficerproductivityhasalwaysbeenanissueforresearchers(Bonkiewicz,2016).Forexample,countingthenumberofcallsforserviceasameasureofpoliceperformancecanbeproblematic,asonecallforservicemighttakeanofficer20minutestodealwith,whileanothermighttaketwoorthreehours.Lookingatthenumberofarrestsortrafficcitationsbyanofficerisproblematicforsimilarreasons.Moreover,countingthenumberofarrestsorticketsissuedisadecentindicationofapoliceoutput,inthatitcanmeasurewhatapoliceofficer

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isdoing,butitiscommonlynotaverygoodindicatorofapoliceoutcomeorameasureofwhateffectthatparticularactionhasonthecrimerateormakingacommunitysafer.Furthermore,authorshavepointedtoanumberofpossibilitiesthatcouldaccountfordifferencesinpoliceofficerproductivity,includingindividualfactors(Shane,2011),operationalvariables,organizationalvariables,andcommunityvariables(Bonkiewicz,2016),makingitdifficulttocompareoneofficertoanother,oronedepartmenttoanother.

Still,itisclearthatthenumberofpoliceofficersinacitycanhaveseriousimplicationsforhowthatpolicedetachmentordepartmentoperates.Thisisoftendescribedintermsofthenumberofpoliceofficerspercapita,orthe‘coptopop’ratio.Havingtoofewpoliceofficersinagivenareacanbeproblematicforanumberofreasons.Forexample,researchershavepositedthatpolicemayresortto‘loadshedding’inahighcrimejurisdictionwithlowpolicingnumbers,whereofficerscontinuetorespondtoandrecordseriouscrimes,butdecidetoletlessseriousoffendersoffwithjustawarningornotrecordthecrimeatallduetotimeandresourceconstraints(Maxfield,Lewis,&Szoc,1980).Others,suchasBonkiewiczhavelookedatthenumberofcrimesperpoliceofficer,or‘crimepercopratio’,toarguethathighcrimecitiesorareasrequirealargerpolicepresencetobeeffective,statingthatthe“crimetocopratiocandramaticallyeffectofficers’productivity”(2016:22).

Oneofthemostcommonresponsestoacrimeproblemwithinacityisthecallforthehiringofmorepoliceofficers.Itislogicaltoassumethatmorepoliceonthestreetwoulddetercrime,anditisoftenapopularstrategywiththepublic,whousuallyfeelsaferwhentheyseemorepoliceonpatrol(Caudill,Getty,Smith,Patten,&Trulson,2013).Similarly,Becker(1968)arguedthatanincreasedpolicepresencewouldraisethelikelihoodofanoffendergettingcaught,whichwouldleadtolowercriminalactivity.However,therelationshipbetweenpoliceandcrimeisnotalwaysanegativerelationship,assomestudieshaveshownthathighernumbersofpoliceofficersoftenhavenoeffectorcanactuallyincreasecrimerates,inthatmorepolicemeanmorecrimeisbeingdetected,whichmeansahighercrimerate,particularlyintheshort-term(Eck&Maguire,2000).Itshouldbenotedthatthesestudieshavebeencriticizedfornotaccountingforthedifferencebetweencorrelationandcausation(Lin,2009).Recentresearchthathasattemptedtocontrolforthecorrelation/causationissuehasoftenfoundthatanincreaseinthenumberofpoliceofficersdecreasescrimebyroughlythesameamount.Inotherwords,a10%increaseinthenumberofpoliceofficerswoulddecreasecrimebyabout10%(Levitt,2002).Withthisinmind,usingcoptopopratiosasapotentialexplanationforvariationsinpropertycrimeratesmustbedonecautiously.

Socio-EconomicFactorsofPropertyCrimeOneoftheleadingexplanationsforpropertycrimerateshashistoricallybeensocio-economicfactors,suchashouseholdincomelevels,unemploymentrates,andeducationlevels.However,crimerateshavenotalwaysfollowedeconomictrends.Instead,therehavebeendifferentperiodsoftimewherestrongeconomicconditionsoccurredduringaperiodofrisingcrimerates,suchasthe1950sand1960s.Conversely,therehavebeenperiodsofpooreconomicconditionsandhighunemploymentratesthathavenotseenacorrespondingincreaseincrimerates,suchasthelate2000sduringtheUS/GlobalFinancialCrisis(Clancey&Lulham,2014).

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LOWINCOMEORPOVERTY

Therelationshipbetweenneighborhoodssufferingfromhighlevelsofpovertyandcrimerateshasoftenbeenthesubjectofcriminologicalstudy.AsChester(1976)pointedout,povertywasseenasacontributingfactortocrimeratessincethetimeofPlatoandAristotle.However,whilesomestudieshavefoundthatpoverty,asmeasuredbyvariablesincludingincomelevelsandproportionofpublichousing,isassociatedwithmorecrime(Shaw&McKay,1942;Chester,1976;Bursik&Grasmick,1993;Ackerman,1998;Peterson,Krivo,&Harris,2000;Hannon,2002),otherstudieshavenotfoundthisrelationship(Slocumetal.,2013;Boessen&Hipp,2015).Thatbeingsaid,itwouldappearthatadultslivinginneighbourhoodswithhigherlevelsofpoverty,socialdisorder,anddisorganizationareathigherriskforengaginginorbeingavictimofcrime,evenafteraccountingfordemographiccharacteristics(Aaltonen,2011;Sciandra,Sanbonmatsu,Duncan,Gennetian,Katz,Kessler,Kling,&Ludwig,2013).Moreover,individualslivinginpovertyareoftenexposedtopropertycrimefarmorethanthoseinthegeneralpopulation(Larsson,2006).Thislargelysupportstheorieslikesocialdisorganization,whichstatethatpovertyweakensacommunity’ssocialbondsandsocialcontrols,leadingtoahigherproportionofcriminaloffendersinacommunity.Thesetypesoffindingsalsofrequentlymentionroutineactivitytheoriesasanexplanationforthisrelationship.Interestingly,asHannon(2002)pointedout,povertycanalsosimultaneouslylessentheopportunitiesforpropertycrimebyreducingthepresenceofworthwhileorvaluabletargetsforoffenders.Thiscouldbe,inpart,anexplanationforsomeofthevariedresultsseenintheresearchliteratureontherelationshipbetweenpropertycrimeandpoverty.

InauniqueresidentialmobilityexperimentfromtheUnitedStates,familieslivinginhigh-povertypublichousinginfivedifferentmajorcities(Baltimore,Boston,Chicago,LosAngeles,andNewYork)weregiventheopportunitytomovetoaless-distressedneighborhoodusingahousingvoucher.Datacollectedfromthisexperimentinitiallyshowedsignificantdecreasesinbothviolentcrimearrests(32%)andpropertycrimearrests(33%)forindividualswhomovedoutofthehigh-povertyneighborhoods(Sciandraetal.,2013).However,followupresearch10yearsaftertheinitialmoveshowednostatisticallysignificantdifferenceinpropertycrimeratesforindividualswhowereselectedtomoveawayfromthehigh-povertyneighborhoods.Thisissimilartotheresultsseeninmanyofthestudiesonsocialdisorganizationpreviouslydiscussed.Theseresultssuggestthatoffendercharacteristicsmayplaymoreofarolethanneighborhoodcharacteristicswhenitcomestopropertycrime,althoughtheresearchsupportingthispositionwaslimitedinscope.

Insum,empiricalfindingsontherelationshipbetweencrimeandpovertyhavebeenmixedoverthepastseveraldecades.Whilesomeresearchhasfoundarelationshipbetweenhighercrimeratesandlowincome,otherresearchhasnotreachedthesameconclusion.Still,mostresearcherswouldagreethataslevelsofpoverty,socialdisorder,andsocialdisorganizationincrease,theriskofengagingincriminalbehaviourorbeingavictimofcrimeincreases.Whileitwouldappearthatthoselivinginpovertyareoftenexposedtopropertycrimeathigherlevelsthanthegeneralpopulation,someresearchhasfoundtheoppositetobetrue.Thiscontradictioniscommonlyexplainedbythenotionthatthoselivinginpovertyandthoselocationscharacterizedasbeinginpovertyoftenhavetheleastvaluableitemstosteal.

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INCOMEINEQUALITY

Relatedtotheissueofpoverty,muchoftheacademicliteraturefocusesnotjustsolelyonindividualpoverty,butonthelevelofinequalitybetweenthepoorandthewealthyinthesamecityorcommunity.Again,thisisnotanewareaofstudy,asearlycriminologists,suchasBonger(1916;ascitedinChester,1976)pointedoutthatpovertyinandofitselfisnotwhatcausescrime.Instead,Bongerarguedthatcrimewascausedbythecontrastbetweenthepoorandtherich.Thishasbeenreflectedinmodernliteratureaswell,whereresearchershaveconsistentlyfoundstrongrelationshipsbetweencrime,particularlypropertycrimeslikeburglary,motorvehicletheft,androbbery,andincomeinequality(Kposowa,Breault,&Harrison,1995;Neumayer,2005;Boessen&Hipp,2015).Interestingly,asChesterpointedout(1978),thisproblemisoftenperpetuatedbyinterpersonalcontactsbetweenthelowerclassandthemiddleorupperclass,andisalsoconstantlydisplayedanddiscussedinthemedia,intelevision,andinmovies.Whetheritistrueornot,itisoftenpointedoutthroughthemediathatanyonecanmovefrom‘ragstoriches’orlivetheAmericandream,butclearlythisdoesnothappentoeveryonelivinginpoverty.Chester(1976)arguedthatitwasthesetypesofinteractionsthatledtofrustration,whichmotivatedthelowerclassestocommitadisproportionatelyhighrateofcrime.Theideaoffrustrationcausedbyeconomicinequalityleadingtocriminalactivity,bothpropertyandviolentcrime,hasbeenrepeatedinnumerousstudies(Hagan&Peterson,1995;Neumayer,2005);however,manyoftheseauthorsalsonotedthattheevidencewasnotalwaysconclusive,andoftenlimitedinsupportoftherelationshipbetweenincomeinequalityandcrime.

Incomeinequality,orthedifferencebetweentheincomesofthewealthyandpoorinthesamejurisdiction,hasbeenshowntohaveastrongeffectonpropertycrimeinthecontemporaryresearchliterature.Inparticular,manyresearchershavefoundthatcrimes,suchasburglary,motorvehicletheft,androbbery,werelinkedtoincomeinequality(Kposowa,Breault,&Harrison,1995;Neumayer,2005;Boessen&Hipp,2015).However,itshouldbenotedthatsomeresearchershavefoundmorelimitedsupportforthisrelationship(Hagan&Peterson,1995;Neumayer,2005).Itislikelythatratherthanbeinganindependentexplanationforpropertycrime,incomeinequalityinteractswithothersocio-economicfactors,suchasemploymentopportunities.

UNEMPLOYMENT

Researchontherelationshipbetweencrimeandunemploymentisextensive,spanningmultipleacademicdisciplines,includingcontributionsfromeconomists,criminologists,sociologists,andmore.Theoreticalliterature,suchassocialdisorganizationtheory,rationalchoicetheory(Becker,1968),orstraintheory(Agnew,1992),typicallyagreedthattherewasapositiverelationshipbetweenunemploymentandcrimeforavarietyofreasons.However,recentempiricalresearchhasbeenfarmoreinconsistent(Cook&Watson,2014).Thereasoningforthisinconsistencyisvaried,withsomepointingtoissueswithdata,whileothersdisputethepropermethodologyormodelingforanalyzingtheissue(Cook&Watson,2014).Basedontheirresearch,CantorandLand(1985)arguedthatunemploymentdidnothavealineareffectoncrime,butthatcrimeoftenincreasedduringtimesoflowunemploymentduetotheopportunityeffect(moredesirableandaccessibletargets),andalsoincreasedduringperiodsofhighunemploymentduetotherelationshipbetween

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crimeandpoverty(e.g.moremotivatedoffenders).Theywentontostatethatopportunityis‘pro-cyclical’,meaningthatcrimecouldincreaseduringgoodtimes,whilemotivationwas‘counter-cyclical’,meaningthatcrimecouldalsoincreaseduringbadtimes(Cantor&Land,1985).Thesefindingsareinlinewiththetheoriesdiscussedpreviously,suchasroutineactivitytheoryandsocialdisorganizationtheory.

Clearly,therelationshipbetweenunemploymentandpropertycrimeisquitemixedintheempiricalliterature.Again,whilesomeresearchershavefoundthathigherratesofunemploymenthavecontributedtohigherratesofpropertycrime(Becker,1968;Agnew,1992),otherresearchhasdrawnmuchmoreinconsistentfindings(CookandWatson,2014).Forexample,whileunemploymentrateswerehighduringthefinancialcollapseintheUnitedStatesin2008,propertycrimeremainedlow.Meanwhile,whenunemploymentrateswereverylowinthe1960s,propertycrimeratesremainedhigh.Thereareseveralpossibleexplanationsforwhypropertycrimeratesremainlowduringtimesofhigherunemployment.Forinstance,itispossiblethatpeopleremainathomemoreoftenwhenunemployedleadingtothepresenceofguardianshipofproperty.Asaresult,lesspropertycrimes,suchasbreakandenterormotorvehicletheft,occur.Alternatively,itisalsopossiblethatduringtimesofhighunemployment,peoplespendlessmoneyonexpensiveitemsthatmightbedesirabletosteal,suchassmallelectronics.Giventhis,itispossiblethatlowunemploymenthastheoppositeeffect.Lowunemploymentlikelyresultsinmorepeoplebeinghomelessoftenandspendingmoremoneyongoodsthatwouldbedesirabletoapropertycrimeoffender.

EDUCATION

Itwouldappearthatalowlevelofeducationisaverypowerfulpredictorofcrime.Forexample,researchhasshownthatover40%ofinmatesinAmericanprisonshadnotcompletedhighschool,comparedtolessthan20%oftheaveragepopulation.Similarly,intheUK,researchhasdemonstratedthatnearly50%ofnewprisonershadnoeducationalqualificationscomparedtojust15%inthegeneralpopulation(Bell,Costa,&Machin,2015).ThisoutcomewasalsofoundbyAaltonen(2011),whoshowedthatlowerlevelsofeducationalattainmentwereoftenassociatedwithhigherlevelsofcrime,andfurtherstatedthateducationandunemploymentwasastrongpredictorofcriminalactivity.LochnerandMoretti(2004)providedsubstantialevidenceoftherelationshipbetweenlowerlevelsofeducationandhigherratesoncrimeanddemonstratedthateachacademicyearofschoolingsuccessivelydecreasedthelikelihoodofincarcerationlaterinlife.Moreover,researchfromtheUnitedKingdomindicatedthat,afterincreasingthehighschoolgraduationagefrom15to16,criminalconvictionsdecreased(Machin,Marie,&Vujic,2011).Evenwhenattemptingtocontrolforothervariables,suchasincome,unemployment,oroccupation,educationhasoftenbeenshowntobeakeyfactorindeterminingcriminalactivity,althoughtheseothervariablesdidhavesomeeffect(Aaltonen,2011;Maynard,Salas-Wright,&Vaughn,2015).

Lowlevelsofeducationareassociatedwithnumeroustypesofcrimes,includingpropertycrime(Aaltonen,2011).Ofcourse,thereissomeoverlapbetweenindividualtraitsrelatedtopooracademicperformanceandcrime.Specifically,individualtraits,suchaslowself-control,lowerintelligence,ortheinabilitytodelaygratification,arelinkedtobothpooracademicperformance

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andcriminalactivity(Aaltonen,2011).Still,onestudyconcludedthathighschooldropoutsweretwotothreetimesmorelikelytogetarrestedfortheftthananindividualwhocompletedhighschool,evenwhencontrollingforotherdemographicvariables(Maynardetal.,2015).

Manyofthesocio-economicfactorsthatareoftendiscussedashavingapossiblelinktopropertycrime,suchasunemployment,poverty,education,residentialmobility,andincomeinequality,havehadmixedfindingsintheempiricalresearchliteratureinthattherearealargenumberofresearcharticlesbothdemonstratingandrefutingarelationshipbetweenoneofthesevariablesandpropertycrimewithinacommunity.Thisissueisespeciallytrueforthevariablesrelatedtolowincome,poverty,andunemployment.Still,onevariablethatwasrepeatedbymultiplesourcesashavingapositiverelationshipwithpropertycrimewasincomeinequality.Severalresearchstudieshavepointedtohigherratesofincomeinequalitybeinglinkedtohigherratesofvarioustypesofpropertycrimeswithinacommunity.Similarly,lowlevelsofeducationalsohadapositiverelationshipwithincreasedpropertycrime,butmanyresearcherscautionedthatlowlevelsofeducationarealsorelatedtootherconfoundingfactors,suchasunemployment,lowincome,oroccupationalsuccess.However,evenwhencontrollingfortheseotherfactors,theresearchsuggeststhatthehighertheproportionofmembersinacommunitywithlowlevelsofeducation,thehigherthatcommunity’spropertycrimerate.

NeighborhoodCompositionRelatingtoPropertyCrimeThefinalmajorcontributingfactorisneighborhoodcompositionandthelevelofsocialdisorganizationinacommunity.Inparticular,researchhasshownstronglinksbetweenillegaldruguse,homelessness,mentalhealthissues,andpropertycrime.However,theseareoftennotdirectcausallinks,butareoftenhighlyinterrelatedtooneanother.Forexample,thehomelesspopulationhasveryhighratesofillegaldruguseandmentalhealthissues,makingitdifficulttodisentangleonefromtheothers.

ILLEGALDRUGUSE

Illegaldruguseisamajorprobleminmanycitiesaroundtheworld,includingNorthAmerica,Europe,Asia,andAustralia.Vancouverisanexampleofthis,withalargeandlong-standingdrugsceneintheDowntownEastSide.Ahighproportionofusersinvolvedinthedruglifestylehavereportedinvolvementineitherpropertycrime,drugcrime,orboth,inanumberofempiricalstudies(Iritani,Hallfors,&Bauer,2007;UnitedNationsOfficeonDrugsandCrime,2009).Infact,onestudyconcludedthatdrugusersoffenduptofourtimesmorethannon-drugusers(Sutherland,Sindicich,Barrett,Whittaker,Peacock,Hickey,&Burns,2015).WilkinsandSweetsur(2010)outlinedseveralreasonswhyfrequentdruguseoftenleadstopropertycrimes.First,the‘drug-crime’modelarguesthatdrugusersresorttopropertycrimestopayforexpensivedrugs.Second,the‘crime-drug’modelpositsthatthecriminallifestyleencouragesdruguse,typicallythroughpeerrelationshipsorpartylifestyles.Third,the‘common-cause’model,statesthatbothdruguseandpropertycrimearecausedbyoverlappingpsychologicalorsocialissues,suchasunemployment,delinquency,orsocialexclusion.Finally,thefourthexplanatorymodeloutlinedbyWilkinsand

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Sweetsur(2010)isthatof‘coincidence’,whicharguesthatdruguseandcrimearenotconnectedinanyway.

Theexactscopeoftherelationshipbetweendruguseandcrimecanbedifficulttomeasure,andcanbespecifictodifferenttypesofdrugsanddifferenttypesofcrime.Forexample,theratesofviolentoffencesvarysubstantiallyfrompropertycrimeoffencescommittedbydrugusers,andsimilarly,drugs,suchasopioids,oftenhaveamuchstrongercorrelationtopropertycrimethanadruglikemarijuana(Sutherlandetal.,2015).Further,whenconsideringthisrelationshipinAustralia,ClancyandLulham(2014)pointedoutthatinternationalevents,suchasthewaronterrorortheinvasionofAfghanistan,ordomesticpolicies,suchastheintroductionofsafeinjectionsites,hadasubstantialimpactontheavailabilityofheroininAustraliathat,inturn,ledtoadeclineintheft,butanincreaseinrobberies.Othershavepointedoutthatitismoreimportanttolookattheamountofmoneyapropertycrimeoffendercangeneratethroughcrimeorwhatfencesorillegalmarketsarepayingforstolenproperty,ratherthansimplylookingattheoverallcrimenumbers.Forexample,ashopliftermayneedtocommitdozensofcrimestogetthesameamountofmoneyassomeoneelsecangetfromjustonerobberyorburglary(Wilkins&Sweetsur,2010).

Whilesomehaveidentifiedzero-tolerancedrugpoliciesasaleadingcauseforcrimeratedecreasesintheUnitedStates,particularlyinproperty-relatedoffences,thesefindingsshouldbetakenwithcaution.ClancyandLulham(2014)pointedout,forexample,thatwhilechangesindrugpolicymayhavecontributedtothedeclineincrime,itwouldnotexplainthelong-termdeclineexperiencedoverthepastdecadeormore.Further,itshouldbenotedthatseveralcountries,includingCanada,haveseensimilardecreasesincrimewithoutzero-tolerancedrugpolicies.Instead,somebelievethatincreasingthefundingfordrugtreatmentandeducationprogramswouldhaveasimilareffectofreducingpropertycrimewithoutthenecessityofputtingdrugusersintoprisons(Wilkins&Sweetsur,2010).Ineffect,theseresearcherspointtonumerousstudiesshowingtheeffectivenessofdrugtreatmentprograms,suchasmethadonemaintenance,asaneffectivewayofreducinglevelsofcriminalactivitybydrugaddictswhiledealingwithaddictionissues.Giventhesefindingsandthefindingsofmanyotherresearchstudies,itremainsunclearthestrengthoftherelationshipbetweenacommunity’spropertycrimerateanditslevelofillicitdruguse.Forexample,theresearchliteratureseemstoindicatethattheratesofillegalmarijuanausewouldlikelyhavelittleeffectonthepropertycrimerateinacommunity,whiletherateofheroinormethamphetamineusewouldlikelyhaveafarmorepositivecorrelationwiththepropertycrimerate.Similarly,propertycrime,suchasmotorvehicletheft,couldprovidefarmoreincomeforanindividualthanshoplifting,inthattheshoplifterwouldlikelyhavetocommitdozensofcrimestocollectthesameamountofmoneyastheindividualsstealingamotorvehicle.

Themajorityofresearcherssupporttheideathatanincreasedrateofdruguse,particularlyharderdrugs,likeheroinormethamphetamines,canleadtohigherratesofpropertycrimewithinacity(Iritani,Hallfors,&Bauer,2007;UnitedNationsOfficeonDrugsandCrime,2009;Sutherlandetal.,2015).Thatbeingsaid,therelationshipcanvarydependingonanumberofvariables,includingthetypeofpropertycrime,thetypeofdrugused,andotherexternalfactors.Asaresult,itisnotsurprisingthatmostresearcherssupporttheapproachofdrugtreatmentandhousingoverenforcementorzero-tolerancepolicies.

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HOMELESSNESS

Researchhasgivenconsiderableattentiontothenumbersofhomelessindividualsinvolvedinthecriminaljusticesystem.Forexample,recentstudiesexaminingprisonpopulationsintheUnitedStateshavefoundthatupwardsof25%ofinmateshavehadahistoryofhomelessness,poorhealth,anddisadvantagedsocioeconomicstatus,roughlysixtimesgreaterthanthegeneralpopulation(McNiel,Binder,&Robinson,2005;Greenberg&Rosenheck,2008),whileothershaveidentifiedhomelessnessasapowerfulpredictorofcrime(Somers,2013).Further,themostcommontypeofcrimecommittedbyinmates,andoffendersmoregenerally,ispropertycrime,whichGreenburgandRosenheck(2008)suggestedwas‘survivalbehavior’.Oneofthebiggestchallengeswhenconsideringtheeffectofacity’shomelesspopulationoncrimeratesisgettinganaccuratecountofthehomeless.Duetothechallengesinherentinthepopulationitself,suchasadistrustofauthority,problemswithdefininghomelessness,aswellasmanymethodologicalissues,gettinganaccuratenumberhasproventobeextremelydifficult(Heerde&Hemphill,2014).Thatbeingsaid,someresearchershaveestimatedthatover500,000peoplearehomelessonanygivennightintheUnitedStates(Fargo,Munley,Byrne,Montgomery,&Culhane,2013).Further,andrelatedtotheearlierdiscussionondrugabuse,researchhasshownhigherratesofdrugusewithinthehomelesspopulation,whichfurthercompoundstheproblem(Fargoetal.,2013).

Althoughexplainingthecausesofhomelessnessisfarbeyondthescopeofthispaper,authorshavepointedtonumerouscauses,suchaspoverty,residentialmobility,highmedianrentcosts,andunemployment(Fargoetal.,2013).GreenbergandRosenheck(2008)outlinedseveralreasonswhythehomelesspopulationhavehigherratesofinvolvementinthecriminaljusticesystem.First,theypointedoutthathomelessnessmaydriveindividualstocrimesimplytosurvive.Second,theyarguedthatthehighratesofdrugabuse,poorhealth,ormentalhealthissuesseeninthehomelesspopulationmayincreasetheirinvolvementinthejusticesystem.Next,theypositedthatsocioeconomicfactors,suchasapooreducation,couldbeacause.Finally,theysuggestedthattherelationshipwasbi-directional,andthatinvolvementinthecriminaljusticesystemcouldcontributetohomelessnessthroughthedamagingoffamilyandcommunitytiesorrestrictionstoemploymentorhousingopportunitiesafterbeingincustody.

Inaddition,theissueofhomelessyouthhasbeencoveredextensivelyintheacademicliterature,particularlyhomelessyouthwhohavesufferedfamilyviolenceorabuse.Thishighlymarginalizedgroupoftenhasanumberofbarrierstofindingsafehousing,includingbasiceducation,employment,ortreatment,whichmightcontributetotheirriskofparticipatinginpropertycrime(Heerde&Hemphill,2016).EstimatesfortheUnitedStatespositedthatbetween1.6and2.8millionadolescentswereconsideredhomeless(Terry,Bedi,&Patel,2010),whileRachlis,Wood,Zhang,Montaner,andKerr(2009)estimatedthatroughly10,000adolescentswerehomelessonanygivennightinCanadain2001.Thisresearchhasalsoshownthathomelessyouthengagedin,andwerevictimsof,numeroustypesofcrime,includingpropertycrimes(Heerde&Hemphill,2014).Forexample,HeerdeandHemphill(2016)estimatedthattwo-thirdsofhomelessyouthhadengagedinatleastoneillegalact.Similartotheadulthomelesspopulation,researchhasalsoshownthatdruguseamonghomelessyouthisconsiderablyhigherthaninthegeneralpopulation(Heerde&Hemphill,2014).

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HalfwayhousesinCanadaareoperatedbyprivate,non-governmentalorganizationsorindividuals,andareusedtohouse15to30adultcriminaloffendersondayparoleinthecommunity.Thesetypesofcommunity-basedhomesareusedinseveralcountriesaroundtheworld,includingtheUnitedStates,UnitedKingdom,Japan,andSingapore(Brown,2010).Thesetypesoffacilitiesareoftenusedtoreintegrateoffendersintobackintothecommunity,orareusedtohouselowriskoffendersasanalternativetoprison.AsBrown(2010)pointedout,halfwayhousesareanimportantpartofthereintegrationprocessforoffenders,whooftenhavetroublesecuringandmaintaininghousinginthecommunityafterreleasefromprison.Italsoallowsforcorrectionstosuperviseandassistinprogrammingforoffendersafterrelease.Brown(2010)alsoarguedthat,althoughthereisverylittleresearchonthesubject,thereisnoevidenceshowingthatthepresenceofacorrectionalhalfwayhousehasaneffectoncrimeratesinthecommunity.However,thereisgrowingconcernthatillegalhalfwayhousesorunlicensedhalfwayhousescanincreaseanoffender’sriskofrecidivism,particularlyarounddrugandpropertyoffences,ratherthanservingasatransitionpointbetweenacriminallifestyleandapro-sociallifestyle.

Themajorityofresearchsupportstheideathathigherratesofhomelessnesscancauseanincreaseinpropertycrimeinaneighborhood(Somers,2013).Thisisanimportantfindingforcitiestryingtodealwithlargehomelesspopulations.Ithasalsobeenpointedoutthattheratesofhomelessnessforindividualssufferingfrommentalhealthissues,and/ordrugaddictionissueshavealsobothbeenlinkedtoincreasedpropertycrimeratesinsomecircumstances.Whethertheseindividualscommitcrimetosurvive,commitcrimetosupportadrughabit,orcommitcrimeduetootherchallenges,suchasalackofeducationoremployment,itisclearthathomelessnesshasapositivecorrelationwithpropertycrimeinacommunity.Thisrelationshipisespeciallytrueforhomelessyouth,whocompriseavulnerableandat-riskgroup.Still,thedebatetendstofocusonthestrengthofthiscorrelation.

MENTALHEALTHISSUES

Oftenrelatedtothepreviousdiscussionofhomelessness,individualswithmentalhealthissuesareatveryhighriskforbeingarrestedorotherwiseinvolvedwiththecriminaljusticesystem(Somersetal.,2013).Infact,itisnotatalluncommontoseevisiblepopulationsofpeoplesufferingfrommentalhealthissuesaspartofthehomelesspopulationintheLowerMainlandofVancouver,BritishColumbia.However,itshouldbenotedthatthereisverylittleevidencetosupporttheideathatthereisadirectcausalrelationshipbetweenmentalhealthissuesandcrime.Instead,asSomersetal.(2013)pointedout,itisfarmorelikelythatthereisanindirectrelationship,overlappingwithotherissues,suchasdrugaddiction,poverty,socialmarginalization,unemployment,orcriminalvictimization.Inthepast,themajorityofthepopulationofmentallyillindividualsweretreatedinhospitals;however,thenumberofbedsavailableinthesefacilitieshascontinuedtodeclineinboththeUnitedStatesandCanada(Markowitz,2010).Ashospitalshaveclosed,themajorityofindividualssufferingfromvariousmentalhealthissuesweredischargedintothecommunity.AsMarkowitz(2010)pointedout,themajorityoftheseindividualssufferingfrommentalhealthissuesendeduplivinginthecommunitywithlittleornosupervisionorsupport,whichcanleadtoanumberofissues,includingcriminalbehavior.Ineffect,itappearsthatthe

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researchliteraturetendstoviewmentalhealthissuesasanadditionalorcontributingfactorinexplainingpropertycrimerates,ratherthanasamainorleadingfactor.

Insum,themajorityoftheresearchliteraturesupportstheideathatneighborhoodcompositioncanhaveaneffectonpropertycrimerates,althoughtovaryingdegrees.Forexample,asdiscussedabove,therelationshipbetweendruguseandthepropertycrimerateinacommunitycanvarydependingonthetypeofdrugused,asstrongernarcotics,suchasheroinandmethamphetamines,havemoreofaninfluencethansofterdrugs,likemarijuana.Mostofthosesameresearcherssupportatreatmentapproachtodealingwiththedrugproblem,ratherthanzero-tolerancepolicies,suchasthoseusedintheUnitedStates.Homelessnesswasalsostronglylinkedtoincreasedpropertycrime,particularlywhenconsideringthehighpercentageofhomelesspeopledealingwithconcurrentdrugaddictionormentalhealthchallenges.Mentalhealthissues,ontheirown,donotappeartodirectlycontributetopropertycrimerates,but,whencombinedwithoverlappingissuesofpoverty,homelessness,addiction,unemployment,ormarginalization,itisclearthatmentalhealthissueswithinacommunityshouldnotbeignoredwhentryingtounderstandpropertycrimerates.

SUMMARYOFTHEORETICALEXPLANATIONSFORPROPERTYCRIMEFLUCTUATIONS

Inconclusion,thereareanumberoftheoriesthatattempttoexplainthecausalfactorsrelatedtopropertycrimeandthesocial,economic,anddemographicvariablesthatcontributetoincreasesordecreasesintherateofpropertycrimeinacommunity.However,onetheorythatdoesprovidesomecontextandcancontributetoanunderstandingofthesignificantincreaseinpropertycrimewitnessedthroughoutNorthAmericainthelate1990s,aswellasthesignificantdropthatoccurredinthe2000s,isroutineactivitytheory,andtherelatedsituationalcrimepreventiontheories(Clancy,2014).Accordingtothesetheories,thedeclineinpropertycrimeinCanadaandtheUnitedStatesoverthepastseveralyearscouldbeexplainedbyanoverallimprovementtopersonalandpropertysecurity,suchashomealarmsorimmobilizersinmotorvehicles,aswellasaheightenedawarenessamongindividualsfortheirownpersonalsafety.Manyoftheseadvancementswerecreatedinresponsetothehighpropertycrimeratesseeninthelate1990s.Immobilizers,forexample,werecreatedinresponsetoskyrocketingmotorvehicletheftrates,andwereimmediatelyshowntobeveryeffectiveinpreventingmotorvehiclethefts.Sincethattime,moreandmoreautomobilemanufacturersincludeimmobilizersasastandardfeatureinnewvehicles,andalongwithanincreasedadoptionrate,motorvehicletheftrateshavesubstantiallydeclined(Clancy,2014).Ofnote,TransportCanadahasmadeimmobilizersmandatoryforallnewvehicles.Ineffect,thesetypesofstrategiesaimtoreducetheopportunityforacriminaltocommitanoffencebymakingiteitherdifficultorimpossibletobesuccessful.

Giventheseinnovations,andthecontributionsofpolice-basedcrimereductionstrategies,itwasnotsurprisingtherehasbeenasignificantdeclineincertaintypesofpropertycrimes,likemotorvehicletheftorbreakandenters,throughouttheLMDinthe2000s.However,thereremainsalargenumberofpropertycrimesthatarerelativelyeasyforanoffendertocommit,suchastheftfromvehicles,othertheftunder$5,000,andmischieftoaproperty,particularlyaroundcommercialareas,wherethegoalistobeopeningandinvitingtopotentialcustomers.Forexample,aparking

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lotfullofmotorvehicleswithownersinsideashoppingmallforextendedperiodsoftimecreatesanexcellentopportunityforpotentialoffenders.Likewise,mischieftopropertycanbemoredifficulttopreventinacommercialareawherefewpeoplearearoundlateatnight,creatinganeasyopportunityforanoffender.Aswillbedemonstratedbelow,itisthesetypesofcrimesthatmakeup,forthemostpart,themajorityofrecentpropertycrimeintheLMD.

MethodologyfortheAnalysisofPropertyCrimein2015in22LowerMainlandDistrictsThedataforthepropertycrimeprofileswasprovidedby“E’DivisionRCMP.Inadditiontothenatureandquantityofpropertycrimeineachjurisdictionin2015,thespecificlocationforeachoffencewasalsoprovided.ThisdatawasgeocodedwithinArcMap.Pointmapswerecreatedtoindicatetheexactlocationwhereeachoffenceoriginatedfrom,whiledensitymapswerecreatedtovisualizethoseareaswiththegreatestconcentrationofoffences.9Allofthedensitymapswerecreatedusingthesamecolorscheme,rangingfromclearrepresentingthelowestlevelofdensity,todarkgreen,lightgreen,yellow,orange,andred,whichrepresentedthehighestlevelofdensityofpropertycrimes.

Intermsofthebivariate,multivariate,andmunicipal-levelanalyses,initsrawform,thepropertycrimeratedemonstratessignificantskew.Asaresult,itwassubjectedtoalogarithmictransformation.Thistransformationwassuccessfulinnormalizingthevariable.Inaddition,thestructuralvariablesusedinthisstudywereallderivedfromthe2011NationalHouseholdSurvey(NHS),whichisthemostup-to-datesourceofcensusinformationinCanada.ThedefinitionofeachofthevariablesisprovidedinTable6.

9Onlythedensitymapsareprovidedinthisreport.Thepointmapswereusedtounderstandthespreadofpropertycrimesthroughoutajurisdiction.

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TABLE6:VARIABLEDEFINITIONS

Variable DefinitionPopulationDensity PopulationpersquarekilometerPopulationChange2006-2011(%) Percentagechangeinpopulationbetween2006and2011YoungMales–Aged15-24(%) Percentageofpopulationcomprisedofmalesaged15-24

Unmarried(%) Percentageofpopulationthatisaged15andoverthatisnotmarriedandnotlivingwithacommon-lawpartner

Mobility-Last5Years(%) Percentageofpopulationthathasmovedintotheareainthepast5yearsImmigration(%) PercentageofpopulationthatwasbornoutsideofCanadaRecentImmigration–LastFiveYears(%)

PercentageofpopulationthatimmigratedtoCanadainthepast5years(2006-2011)

RecentImmigration–LastTenYears(%)

PercentageofpopulationthatimmigratedtoCanadainthepast10years(2001-2011)

VisibleMinority(%) Percentageofpopulationcomprisedofpersons,otherthanaboriginalpeoples,whoarenon-Caucasianinraceornon-whiteincolour

Non-Citizens(%) Percentageofpopulationthatisnon-permanentresidentsLinguisticIsolation(%) PercentageofpopulationthatcannotspeakEnglishorFrench

AboriginalPopulation(%)

Percentageofpopulationthatisaboriginal.AboriginalreferstopersonsthatareFirstNations(NorthAmericanIndian),MétisorInuk(Inuit)and/orareRegisteredorTreatyIndian,(thatis,registeredundertheIndianActofCanada)and/oraremembersofaFirstNationorIndianband

MedianHouseholdIncome MedianincomeofhouseholdsLowIncomeFamilies(%) PercentageoffamiliesthatarecharacterizedaslowincomeaftertaxUnemploymentRate Percentageofpopulationthatisaged15andoverthatisnotemployed

LabourForceParticipation(%) Percentageofpopulationthatisaged15andoverthatisnotinthelabourforce

LessThanHighSchoolEducation(%) Percentageofpopulationthatisaged15andoverthatdidnotcompletehighschool

Renters(%) Percentageofhouseholdsthatrenttheirdwellings

HousingCondition-MajorRepairs(%)

Percentageofoccupiedprivatedwellinginneedofmajorrepairs.Forexamplesofmajorrepairs,pleaseconsulthttps://www12.statcan.gc.ca/nhs-enm/2011/ref/guides/99-014-x/99-014-x2011007-eng.cfm

Theunitsofanalysisfortheanalysespresentedbelowaredisseminationareas(DA).Disseminationareasaresmallareascomposedofoneormoreneighbouringdisseminationblocks,withapopulationof400to700persons.Itisthesmalleststandardgeographicareaforwhichallcensusdataaredisseminated.AllofCanadaisdividedintodisseminationareas.

Thefirststepinunderstandingtheeffectofanyvariableistoanalyzeitaloneinrelationtothedependentvariableofinterest,inthisinstancepropertycrimerates.Thisisthefunctionofthebivariateanalyses.Intheseanalyses,eachvariableisanalyzedseparatelyinrelationtopropertycrimerates.But,togetamoreaccurateestimateofthe“real”effectsofeachvariable,theymustbeanalyzedsimultaneouslyinthesamemodel.Thisisthepurposeofthemultivariateanalysispresentedinthisreport.Becausethedatausedforboththebivariateandmultivariateanalyseswereclustered,inthatdisseminationareasareclusteredwithinmunicipalities,theywereanalyzedusingmixedeffectsmodelingtechniques.

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Whilethebivariateandmultivariateanalysesaredesignedtoprovideassessmentsattheaggregatelevel,itstandstoreasonthatthereislikelytobevariationineffectsacrossdifferentmunicipalities.Asaresult,separateanalysesfor21municipalitieswasconducted.Theanalysesconsistedoft-tests,comparingpropertycrime“hotspots”andhighvolumeareaswith“non-hotspots”ineachmunicipality.Thehotspotswerederivedfromthedensitymapspresentedlaterinthisreport.Thedisseminationareaswiththehighestconcentrationsofpropertycrimeweredesignatedashotspots,whileallotherdisseminationsweredesignatedasnon-hotspots.Thet-testanalysesthencomparedthevariousstructuralvariablestoseeifthereweresignificantdifferencesbetweenhotspotandnon-hotspotareas.Becausetherangeofdisseminationareasthatcompriseeachmunicipalityisquitedisparate,andsomemunicipalitieshaverelativefewDAs,statisticalsignificanceisreportedatboththestandardp<.05levelandthemoregenerousp<.10level.

BivariateandMultivariateAnalysesofPropertyCrimeintheLMDin2015Theresultsofthebivariateanalysesarepresentedinthe“Bivariate”columnsinTable7.The“Effect%”columnprovidesanindicationofthesizeoftheeffectofeachvariableonpropertycrimerates.Forexample,theeffectsizeforunmarriedis3.07%,meaningthatforeveryone-unitincreaseinthepercentageofunmarriedindividualsinadisseminationarea,thepropertycrimerateisexpectedtoincreaseby3.07%.Conversely,avariablesuchasimmigrationisnegativelyrelatedtopropertycrime.Inotherwords,everyone-unitincreaseinthepercentageofimmigrantsisanticipatedtoreducethepropertycrimerateby0.67%.

Therearetwovariablesthatmeritspecialattentionbecausetheyaremeasuredondifferentscales.First,thecoefficientforpopulationdensityhasbeenmultipliedby1,000torepresentpersonspersquarekilometer.Thus,thevalueof-6.16indicatesthatforevery1,000-unitincreaseinpopulationdensity,therateofpropertycrimeispredictedtodecreaseby6.16%.Second,thecoefficientformedianhouseholdincomehasbeenmultipliedby10,000.Here,forevery$10,000increaseinmedianhouseholdincome,propertycrimeshouldgodownby6.34%(seeTable7).

Accordingtothebivariateresults,mostofthestructuralvariablestestedshowedastatisticallysignificantrelationshipwithpropertycrimerates(seeTable7).Onlyfourvariablesfailedtoreachthelevelrequiredtobeconsideredstatisticallysignificance.Thesevariableswerethepercentageofrecentimmigrants(lastfiveyears),thepercentageofnon-citizens,unemploymentrate,andlabourforceparticipation.Moreover,mostofthesignificantvariablesproducedresultsintheexpecteddirection.Forexample,eachofthefollowingvariablesrevealedasignificant,positiveassociationwithpropertycrime;populationchange(0.17),proportionunmarried(3.07),residentialmobility(1.23),lowincomefamilies(1.16),lessthanhighschooleducation(0.41),renters(0.88),andpoorhousingcondition(1.13).Putanotherway,aseachofthesevariablesincreased,thelevelofpropertycrimeintheareawasalsoexpectedtoincrease.Thepercentageofthepopulationthatself-identifiedasAboriginalwasalsorelatedtoanincreaseinpropertycrimeinthebivariateanalysis.However,thisrelationshipispotentiallyspuriousandlikelyreflectstheconfluenceofothersocialandeconomicindicators.Thispossibilitywillbeexploredfurtherinthemultivariateanalysis.

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TABLE7:EFFECTSOFSTRUCTURALVARIABLESONPROPERTYCRIMERATES(LOGGED)

BivariateModels MultivariateModel Effect(%) tvalue Effect(%) tvaluePopulationDensity -1.41 -6.16* -4.13 -17.54*PopulationChange2006-2011(%) 0.17 4.33* 0.09 2.44*YoungMales-Aged15-24(%) -5.40 -9.29* -2.99 -5.06*Unmarried(%) 3.07 21.28* 2.49 11.62*Mobility-Last5Years(%) 1.23 15.75* 0.86 8.81*Immigration(%) -0.67 -7.44* -0.44 -4.45*RecentImmigration-LastFiveYears(%) -0.40 -1.90 RecentImmigration-LastTenYears(%) -0.31 -2.26* VisibleMinority(%) -0.44 -7.50* Non-Citizens(%) 0.26 1.72 LinguisticIsolation(%) -1.54 -6.09* AboriginalPopulation(%) 1.82 5.72* -0.25 -0.81MedianHouseholdIncome -6.34 -14.05* -1.45 -2.27*LowIncomeFamilies(%) 1.16 10.27* UnemploymentRate 0.38 1.81 -0.37 -1.85LabourForceParticipation(%) -0.09 -0.80 -0.07 -0.61LessThanHighSchoolEducation(%) 0.41 2.80* 0.26 1.69Renters(%) 0.88 16.00* 0.16 2.11*HousingCondition-MajorRepairs(%) 1.13 6.25* 0.34 2.02**p<.05

Althoughitscoefficientwasnegative,theeffectofmedianhouseholdincomewasintheexpecteddirection;thatis,lowerlevelsofmedianincomewereassociatedwithhigherlevelsofpropertycrime(seeTable7).However,thereweretwoothervariablesthathadsignificantnegativeeffectsthatwerehardertoexplain,namely,populationdensityandtheproportionofyoungmales.Conventionalwisdomwouldsuggestthatbothoftheserelationshipsshouldbepositive,aspropertycrimeratesareexpectedtobehigherinareasthataremoredenselypopulatedandthathaveagreaterconcentrationofyoungmales.Here,theresultsindicatedtheopposite,thatincreasesinpopulationdensityandyoungmaleswereassociatedwithlowerratesofpropertycrime.Theeffectfordensitymayreflectaggregationbias.Ineffect,inthemunicipal-levelanalysisthatwillbepresentedinthenextsectionofthereport,theeffectofdensitywasgenerallypositive.Theeffectofyoungmaleswasmoreconsistentacrossthevariousanalysesandthushardertoexplain.Unlikeviolentcrime,thedistributionofpropertycrimewasnotclearlyconcentratedamongyoungermales.Perhapspropertycrimeismoreequallydistributedacrossagecategories,orisbiasedtowardthoseover25yearsofage.Thisispossibleasmanyofthemostcommonpropertycrimesmaybecommittedbyasmallnumberofprolificoffenders,whotendtobesomewhatolder,morecommonlyaround32to36yearsold.Becausethisvariableisstatisticallysignificant,itwasretainedacrossallremainingmodels,butbecausethiseffectremainspoorlyunderstood,itisnotdiscussedinthosemodels.

TheotherunexpectedbutnoteworthyfindinginTable7isthesignificantnegativerelationshipbetweenvariousindicatorsofimmigrationandpropertycrime.Traditionalcriminologicaltheorizing,particularlyasitrelatestosocialdisorganization,assumesthatthedisruptiveand

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destabilizinginfluenceofimmigrationisaprimarycontributortorisingcrimerates.However,researchhascastconsiderabledoubtonthisperspective,arguinginsteadthatimmigrationcan,infact,havesubstantiallyprotectiveeffectsthatworktoreducecrime(Davies&Fagan,2012).Thisalternativeapproachisoverwhelminglysupportedbythefindingsinthisstudy.Withtheexceptionofrecentimmigration(lastfiveyears),whichwasinsignificant,allofthe“immigration-related”variables,includingvisibleminoritiesandlinguisticisolation,weresignificantly,butnegativelyassociatedwithpropertycrime.Overall,asimmigrationlevelsgoup,propertycrimeratesgodown.Unfortunately,thevariousindicatorsofimmigrationarehighlycorrelatedwithoneanotherand,therefore,cannotbeincludedinthesamemultivariatemodel.Forthisreason,themostgeneralvariable,immigration,wasselectedtorepresentalltheimmigration-relatedvariables.Forthesamereasonofmulticollinearity,thevariablelowincomefamilies,whichcorrelatedwithmedianhouseholdincome,wasalsodroppedfromthemultivariateanalysis.

Bivariateanalysesareusefulforestablishbaselineeffects.Insimpleterms,theytellushowanindependentvariableofinterestisrelatedtoadependentvariable,inthiscasethepropertycrimerate.But,bivariateanalysesareunabletocapturetherichcomplexityofsocialconditions.Moreprecisely,variablesdonotoperateinavacuum.Toproperlyestimatetheeffectsofagivenvariable,itisnecessarytocontrolfortheeffectsofothervariablesthatmayalsoexplainthephenomenonofinterest.Thiscontrollingofeffectsisaccomplishedviamultivariatemodeling.Insteadofcomparingvariablestopropertycrimeratesoneatatime,inthemultivariateanalysis,allofthevariablesareconsideredsimultaneously.Otherwise,theinterpretationofresultsremainsverymuchthesameaswiththebivariateanalyses.Forexample,theeffectofimmigrationunderthe“MultivariateModel”columninTable7of–0.44%wouldbeinterpretedasfollows:controllingforalloftheothereffectsinthemodel,aone-unitincreaseintheproportionofimmigrantsisexpectedtolowerpropertycrimeratesby0.44%.

Ineffect,Table7demonstratesthat,whiletheeffectsizesofeachthevariableswerereducedinthemultivariatemodel,almostallofthevariablesremainstatisticallysignificant.TheonlytwovariablesthatdroppedtoinsignificanceweretheproportionofAboriginalresidentsandtheproportionofresidentswithlessthanahighschooleducation.Asnotedearlier,theeffectofAboriginalpopulationinthebivariatemodelwaslikelyanartifact.Whenothersocialandeconomicindicatorsareincluded,Aboriginalpopulationwasnolongerrelatedtopropertycrime.Similarly,itispossiblethattheeffectoffailingtograduatefromhighschoolismediatedbyothereconomicmeasures.Althoughthesevariableshavebeenreducedtoinsignificance,theyarenonethelessretainedinthemunicipal-levelanalysesthatfollowbecause,whiletheyarenotstatisticallysignificantintheaggregate,theymayhaveanimpactatthedisaggregatedlevel.Thislogicunderliesthedecisiontokeepunemploymentandlabourforceparticipationinthemodel,eventhoughtheywerenotsignificantineitherthebivariateormultivariatecontext.

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Municipal-LevelAnalysesofPropertyCrimein2015Thissectionofthereportwillpresentthepropertycrimeprofileof21LowerMainlandDistrictsconsideredinthisreport.10Inadditiontotheprofile,densitymapswillbediscussedtoindicatewherepropertycrimehotspotsexistwithineachmunicipality.Analysescomparingthesocio-demographicandsocio-economiccharacteristicsofpropertycrimehotspotstootherpartsofeachmunicipalitywillbeprovidedtosuggestsomeexplanationsforthedistributionandvolumeofpropertycrimeineachmunicipality.

ABBOTSFORD

In2015,Abbotsfordhad6,744propertycrimesorapproximately18.5propertycrimesperday.Byvolumealone,Abbotsfordrankedsixthoutofthe21jurisdictionsconsideredinthisreport.Themostcommontypesofpropertycrimeweretheftfromvehicle(24.4percent),mischieftoproperty(16.6percent),andothertheftunder$5000(12.4percent).Thiswasfollowedbyautotheft(9.4percent)andshoplifting(8.9percent).Onaverage,inatypicalday,AbbotsfordPoliceDepartmentrecorded4.4theftsfromvehicles,threemischiefstoproperty,2.3othertheftunder$5,000,and1.7autothefts,inadditiontoalltheotheroffencetypespresentedinTable8.Whilebelievedtobeoneofthetypesofpropertycrimesunderreportedtothepolice,AbbotsfordPoliceDepartmentrecorded531fraudsin2015.Intermsofthemoreseriouspropertycrimes,whiletherewere629autotheftsin2015,therewerealso410breakandentersofaresidence,260breakandentersofabusiness,and235breakandenters‘other’.Combiningallthedifferenttypesofbreakandenters,AbbotsfordPoliceDepartmentrecorded2.8breakandentersperday.Finally,therewerealsoasubstantialnumberofarsons(n=35)andasmallnumberoftheftsover$5,000(n=47)in2015.Still,ineffect,approximatelythree-quarters(75.8percent)ofallpropertycrimewasofamoreminornatureinAbbotsfordin2015.11

10Fortheseanalyses,UBCVancouverwasremovedastheirgeographywascoveredintheanalysesconductedfortheCityofVancouver.

11Includedinthecategoryoflessseriouspropertycrimesforallthecitiesdiscussedinthisreportweretheftfromvehicles,mischieftoproperty,othertheftunder$5,000,shoplifting,fraud,biketheft,andpossessionofstolenproperty.Thiswasdonetodistinguishthesetypesoffencesfromautotheft,breakandenter,othertheftover$5,000,andarson.

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TABLE8:PROPERTYCRIMEPROFILEFORABBOTSFORDIN2015

RawNumber(n=6,744) %ofTotal

TheftFromVehicle 1,633 24.4%MischieftoProperty 1107 16.6%OtherTheftUnder$5,000 829 12.4%AutoTheft 629 9.4%Shoplifting 596 8.9%Frauds 531 7.9%Break&Enter–Residence 410 6.1%BikeTheft 284 4.3%Break&Enter–Business 260 3.9%Break&Enter–Other 235 3.5%PossessionofStolenProperty 86 1.3%OtherTheftOver$5,000 47 0.7%Arson 35 0.5%

AsdemonstratedinFigure6,propertycrimewasconcentratedinthemiddleofthecity.Thereweretwomainhotspotsforpropertycrimein2015inAbbotsford.WhilethebulkofpropertycrimeextendedfromMt.LehmaninthewesttoSumasMountainintheeastandfromTrans-CanadaHighwayinthesouthtoDownesRoadinthenorth,thefirsthotspotwasalongGladwinRoadrightuptoMillLakeRoadandbetweentheareajustsouthofSouthFraserWaytojustnorthofGeorgeFergusonWay.Ineffect,thishotpotwasintheClearbrookcommercialarea.Thesecondmainhotspotwasnearby,justtothewestofthefirsthotspot;namely,theareaalongSouthFraserWaybetweenTretheweyStreetandGardenStreetandSimonAvenueandHillcrestAvenue.ThesetwohotspotsweresurroundedbyanareaofhighconcentrationforpropertycrimethatcontinuedalongSouthFraserWaytobeyondClearbrookRoadtothewest.TherewasalsoanemerginghotspotintheareabetweenOldYaleRoadandMaclureRoadandClearbrookRoadandTretheweyStreet.AfinalhighconcentrationofpropertycrimewasfoundintheareajusttotheeastofMcCallumroadaroundJubileeParkandextendingtoGeorgeFergusonWayandWestRailwayStreet.

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FIGURE6:PROPERTYCRIMEHOTSPOTSINABBOTSFORDIN2015

ThereareseveralvariablesthatshowcleareffectswithregardstopropertycrimeinAbbotsford(seeTable9).Forexample,thepercentagesofunmarriedindividuals,mobility,andtheproportionofhousingsneedingmajorrepairsareallpositivelyrelatedtopropertycrimehotspots.Thatis,alloftheseindicatorsaresignificantlyhigherinhighdensitypropertycrimeareasandinthehotspot,asopposedtothenon-hotspotareasofthecity.Moreover,medianhouseholdincomeandlabourforceparticipationarebothsignificantlylowerinhotspotsareas.Finally,twovariables,theunemploymentrateandtheproportionofpeoplewhoself-identifyasAboriginalwasmarginallysignificantlyhigherinthehigherconcentrationareas,althoughtheabsolutenumbersforAboriginalpopulationwasverylowinboththehotspotandthenon-hotspotareasinAbbotsford.Althoughtheproportionofrenters,aswellaspopulationdensity,washigherinthehotspotareas,thedifferenceswithnon-hotspotareaswerenotstatisticallysignificant.Giventhatratesofimmigrationandlessthanhighschooleducationwasvirtuallythesameacrosstheentirecity,itisnotsurprisingthatthesevariableswereinsignificantwhencomparingthepropertycrimehotspotstotherestofthecity.

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TABLE9:COMPARISONOFPROPERTYCRIMEHOTSPOTSANDNON-HOTSPOTS–ABBOTSFORD

Hotspots Non-Hotspots tvaluePopulationDensity 4,116 2,969 1.43PopulationChange2006-2011(%) 11.6% 4.2% 1.46YoungMales-Aged15-24(%) 4.7% 7.2% -3.94**Unmarried(%) 51.8% 38.2% 5.41**Mobility-Last5Years(%) 54.3% 41.7% 2.73**Immigration(%) 25.9% 24.6% 0.30AboriginalPopulation(%) 4.5% 2.6% 1.66MedianHouseholdIncome($) $37,171 $73,027 -8.86**UnemploymentRate 12.4 6.5 1.82*LabourForceParticipation(%) 49.4% 68.1% -3.03**LessThanHighSchoolEducation(%) 17.6% 14.4% 0.63Renters(%) 30.8% 22.1% 1.43HousingCondition-MajorRepairs(%) 6.5% 2.1% 2.25***p<.10;**p<.05

BURNABY

In2015,Burnabyhadatotalof11,865propertycrimes,orapproximately32.5propertycrimesperday.Bythevolumeofpropertycrime,Burnabyrankedthirdoutofthe21jurisdictionsconsideredinthisreport.SimilartoAbbotsford,themostcommonpropertycrimesweretheftfromvehicle(26.1percent)andmischieftoproperty(15.8percent).Shoplifting(13.4percent),theftunder$5,000(12.3percent),andbreakandenterofaresidence(7.8percent)roundedoutthetopfivepropertycrimesinBurnabyin2015(seeTable10).Ofnote,breakandenterofaresidencewasthefifthmostcommonpropertyoffenceinBurnabyin2015.Moreover,thesefiveoffencetypescomprisedthree-quarters(75.4percent)ofallpropertycrimesinBurnabyin2015.Inconsideringthesefiveoffencetypes,onaverage,inatypicalday,theBurnabyRCMPrecorded8.5theftsfromvehicles,5.1mischieftopropertyoffences,4.3shopliftingoffences,fourothertheftsunder$5,000,and2.5breakandentersofaresidence.

Intermsofthemoreseriouspropertycrimes,theBurnabyRCMPrecorded916breakandentersofaresidence,697autothefts,676breakandentersofabusiness,195‘other’breakandenters,55arsons,and54othertheftsover$5,000.Giventhis,theBurnabyRCMPrecorded4.9breakandentersperday,andthemoreseriousformsofpropertycrimecomprisedmorethanone-fifth(22.1percent)ofallpropertycrimeinBurnabyin2015.

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TABLE10:PROPERTYCRIMEPROFILEFORBURNABYIN2015

RawNumber(n=11,865) %ofTotal

TheftFromVehicle 3,084 26.1%MischieftoProperty 1,858 15.8%Shoplifting 1,580 13.4%OtherTheftUnder$5,000 1,448 12.3%Break&Enter–Residence 916 7.8%Frauds 904 7.7%AutoTheft 697 5.9%Break&Enter–Business 676 5.7%BikeTheft 251 2.1%Break&Enter–Other 195 1.7%PossessionofStolenProperty 72 0.6%Arson 55 0.5%OtherTheftOver$5,000 54 0.5%

WhilepropertycrimesoccurredthroughoutmostpartsofthecityofBurnaby,therewasonlyonemajorhotspot.ThishotspotwasfocusedintheareaaroundtheMetropolisMallatMetrotown(seeFigure7)and,asexpected,therewereelevatedratesofpropertycrimeintheareassurroundingthemall.Giventhatpropertycrimewasfoundthroughoutthecity,itisimportanttonotethattherewerehigherconcentrationsofpropertycrimeallalongKingswayHighwayacrosstheentirecityofBurnaby,withincreasedlevelsofpropertycrimeintheareaaroundwhereNorthRoadandAustinRoadintersectwithLougheedHighway,whichisacommercialandshoppingareawithmanystripmallsoroutdoormalls,includingLougheedTownCentre,andtheareawhereKingswayAvenueintersectswithEdmondStreetandWalkerAvenue.

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FIGURE7:PROPERTYCRIMEHOTSPOTSINBURNABYIN2015

ThemostnotablepredictorofpropertycrimeinBurnabywasmedianhouseholdincome,which,inhotspotareas,wasbarelyhalfofwhatitwasinnon-hotspotareas(seeTable11).Mobilitywassignificantlyhigherinhotspots,whilelabourforceparticipationwaslower.Perhapsthemostinterestingfindingconcernsimmigration.RatesofimmigrationarecomparativelyhighBurnabyincomparisontotheothermunicipalitiesinthisstudy.Moreover,thepercentageofimmigrantsinhotspotswasmorethanone-third(34percent)higherinhotspotareaswhencomparedtotherestofthecity.Severalothervariablesweremarginallysignificantinaccountingforpropertycrime.HotspotareasinBurnabyweremuchmoredenselypopulatedandhadhigherproportionsofbothrentersandhousinginneedofmajorrepairs.Fortheremainderofthevariables,thedifferencesbetweenhotspotandnon-hotspotareaswerenotsignificant.Inmostcases,thelackofdifferencewasreadilyapparent.Withtheexceptionofpopulationchange,noneoftheinsignificantvariables

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showedmorethanatwo-pointdifferencewhencomparingthehigherconcentrationofpropertycrimeareastothelowerconcentrationareas.

TABLE11:COMPARISONOFPROPERTYCRIMEHOTSPOTSANDNON-HOTSPOTS–BURNABY

Hotspots Non-Hotspots tvaluePopulationDensity 21,994 6,021 2.35*PopulationChange2006-2011(%) 18.9% 8.8% 0.76YoungMales-Aged15-24(%) 6.0% 7.1% -1.30Unmarried(%) 42.1% 43.8% -0.60Mobility-Last5Years(%) 58.7% 40.7% 2.77**Immigration(%) 66.4% 49.5% 3.52**AboriginalPopulation(%) 0.0% 0.8% -0.96MedianHouseholdIncome($) $35,602 $67,167 -9.22**UnemploymentRate 8.3 6.3 0.79LabourForceParticipation(%) 54.1% 63.5% -2.49*LessThanHighSchoolEducation(%) 5.2% 6.6% -0.51Renters(%) 50.4% 32.9% 1.69*HousingCondition-MajorRepairs(%) 9.3% 4.2% 1.70**p<.10;**p<.05

CHILLIWACK

In2015,Chilliwackhad6,307propertycrimesor17.3propertycrimesperday.Byvolume,Chilliwackrankedseventhoutofthe21jurisdictionsconsideredinthisreport.GivenitsproximitytoAbbotsford,itwasnotsurprisingthatthepropertycrimeprofileinChilliwackwasverysimilartotheprofileforAbbotsford.Themostcommontypesofpropertycrimeweretheftfromvehicle(22.7percent),mischieftoproperty(17.9percent),andotherunder$5000(15.0percent).Thiswasfollowedbyshoplifting(9.9percent)andautotheft(8.0percent).Ineffect,inatypicalday,onaverage,theRCMPrecorded3.9theftsfromvehicles,3.1mischiefstoproperty,2.6othertheftsunder$5,000,and1.4autothefts,inadditiontoalltheotheroffencetypespresentedinTable12.Intermsofthemoreseriouspropertycrimes,inadditiontothe505autotheftsin2015,therewerealso315breakandentersofaresidence,259breakandentersofabusiness,and162breakandenters‘other’.Takingallthebreakandenterstogether,theRCMPrecorded,onaverage,twobreakandentersperday.Finally,therewerealsoalargenumberofarsons(n=80)andasmallnumberoftheftover$5,000(n=31)in2015.Ineffect,excludingthemoreserioustypesofpropertycrime,slightlymorethanthree-quarters(78.3percent)ofallpropertycrimewasofamoreminornatureinChilliwackin2015.

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TABLE12:PROPERTYCRIMEPROFILEFORCHILLIWACKIN2015

RawNumber(n=6,307) %ofTotal

TheftFromVehicle 1,425 22.7%MischieftoProperty 1,126 17.9%OtherTheftUnder$5,000 945 15.0%Shoplifting 623 9.9%AutoTheft 505 8.0%Frauds 446 7.1%Break&Enter–Residence 315 5.0%BikeTheft 272 4.3%Break&Enter–Business 259 4.1%Break&Enter–Other 162 2.6%PossessionofStolenProperty 85 1.4%Arson 80 1.3%OtherTheftOver$5,000 31 0.5%

Whiletherewasasmallamountofpropertycrimefoundthroughoutthecity,asdemonstratedinFigure8,forthemostpart,propertycrimeswereconcentratedthroughoutthemiddleofChilliwackasdefinedbyYaleRoadtothenorthoftheTrans-CanadaHighwayandVedderRoadtothesouth.Moreover,thereweretwomainhotspotsforpropertycrimeinChilliwackin2015.ThesmallerofthetwohotspotswasfoundalongVedderRoadjustsouthoftheTrans-CanadaHighwaytoLuckakuckWay,whichisaverycommercialareacharacterizedbyoutdoorshoppingmalls,bigboxstores,andrestaurants.ThesecondhotspotwasalongYaleRoadfromChilliwackProperVillageWesttoYoungRoad.Ascommonlythecase,thishotspotwassurroundedbyanotherareaofhighvolumeforpropertycrimethatextendedtotheareasnearYaleRoadtoBroadway.

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FIGURE8:PROPERTYCRIMEHOTSPOTSINCHILLIWACKIN2015

AsdemonstratedinTable13,themajorityofvariableshighlightsignificantdifferencesbetweenhotspotandnon-hotspotareasinChilliwack.Insomeinstances,thesedifferencesweresubstantial.Forexample,Chilliwackpropertycrimehotspotswerecharacterizedbyhavingthreetimestheunemploymentrateandmorethanthreetimesthenumberofrenterswhencomparedtonon-propertycrimehotspots.Theyalsofeaturedrelativelyhighlevelsofresidentialmobilityandthenumberofpeoplewholivedintheareathatwereunmarried.Inaddition,themedianhouseholdincomeinpropertycrimehotspotswasonlyaboutone-thirdtheincomeofthoselivinginnon-hotspotneighborhoods.Alloftheserelationshipswerestatisticallysignificant.Onlyfourofthevariablestestedwerefoundtonotdistinguishpropertycrimehotspotsfromnon-propertycrimehotspotsinChilliwack.ThepercentageofimmigrantswasvirtuallyidenticalacrossallareasinChilliwack.Incontrasttomostoftheothermunicipalitiesfeaturedinthisreport,therateofpopulationchangewasactuallylowerinpropertycrimehotspotareas,butthisdifferencewasnotstatisticallysignificant.Hotspotareasexhibitednearly2½timesthenumberofpropertiesinneedofmajorrepairs,andaboutan80%higherrateofbeingpopulatedwiththosewhofailedtocompletehighschool,butneitherofthesedifferenceswerestatisticallysignificant.

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TABLE13:COMPARISONOFPROPERTYCRIMEHOTSPOTSANDNON-HOTSPOTS–CHILLIWACK

Hotspots Non-Hotspots tvaluePopulationDensity 3,721 1,954 2.79**PopulationChange2006-2011(%) 6.6% 10.0% -0.37YoungMales-Aged15-24(%) 5.6% 7.0% -2.19**Unmarried(%) 61.5% 39.3% 7.50**Mobility-Last5Years(%) 57.6% 43.5% 2.42**Immigration(%) 10.8% 12.6% -0.85AboriginalPopulation(%) 19.9% 6.5% 2.42**MedianHouseholdIncome($) $22,515 $64,203 -15.56**UnemploymentRate 14.4 4.8 2.72**LabourForceParticipation(%) 41.7% 64.7% -5.95**LessThanHighSchoolEducation(%) 22.4% 12.2% 1.52Renters(%) 66.8% 19.9% 7.20**HousingCondition-MajorRepairs(%) 9.4% 3.8% 1.53*p<.10;**p<.05

COQUITLAM

In2015,Coquitlamhad5,750propertycrimesor15.8propertycrimesperday.Justbyvolume,Coquitlamrankedeighthoutofthe21jurisdictionsconsideredinthisreport.Verysimilartotheprofilespresentedabove,themostcommontypesofpropertycrimeweretheftfromvehicle(33.5percent),mischieftoproperty(14.6percent),andotherunder$5000(12.2percent).Thiswasfollowedbyshoplifting(10percent),andfraud(6.5percent).Intotal,thesefiveoffencetypescomprisedthree-quarters(76.8percent)ofallpropertycrimesinCoquitlamin2015.Onaverage,inatypicalday,theCoquitlamRCMPrecorded5.3theftsfromvehicles,2.3mischiefstoproperty,1.1theftsunder$5,000,andjustunderoneautotheftperday,inadditiontoalltheotheroffencetypespresentedinTable14.Intermsofthemoreseriouspropertycrimes,inadditiontothe362autothefts,therewerealso362breakandentersofaresidence,296breakandentersofabusiness,and97breakandenters‘other’inCoquitlamin2015.Takingallthebreakandenterstogether,theCoquitlamRCMPrecorded2.1breakandentersperday.Finally,therewerealsoanumberofarsons(n=28)andasmallnumberofothertheftover$5,000(n=22).Ineffect,excludingthemoreserioustypesofpropertycrime,nearlyfour-fifths(79.7percent)ofallpropertycrimewasofamoreminornatureinCoquitlamin2015.

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TABLE14:PROPERTYCRIMEPROFILEFORCOQUITLAMIN2015

RawNumber(n=5,750) %ofTotal

TheftFromVehicle 1,922 33.5%MischieftoProperty 837 14.6%OtherTheftUnder$5,000 698 12.2%Shoplifting 573 10.0%Frauds 373 6.5%AutoTheft 362 6.3%Break&Enter–Residence 362 6.3%Break&Enter–Business 296 5.2%BikeTheft 126 2.2%Break&Enter–Other 97 1.7%PossessionofStolenProperty 43 0.7%Arson 28 0.5%OtherTheftOver$5,000 22 0.4%

GiventhegeographiclayoutandtheconcentrationofcommercialandresidentialareasinCoquitlam,itwasnotsurprisingthatpropertycrimewasdenselyconcentratedinthesouth-westernpartofthecity.AsdemonstratedinFigure9,therewasonemajorhotspotforpropertycrimeinCoquitlamin2015,butseveralemerginghotspotsorareasofsignificantconcern.ThehotspotextendedalongLougheedHighwayfromtheeasternborderofCoquitlampastMarinerWaytothesouthandJohnstonStreet.ItincludedCoquitlamCentreshoppingmallandtheareassurroundingthemallinalldirections.Unsurprisingly,theareaaroundthehotspotalsohasahighdegreeofpropertycrimeandincludedtheCoquitlamCentraltrainstationandtheEvergreenLinestationtothesouth,andcontinueduptoGlenDrivetothenorthofCoquitlamCentremall.

Inadditiontothemainhotspot,therearethreeotherhighvolumepropertycrimeareasinCoquitlam.OnewaslocatedinAustinHeightstothesouth-eastoftheVancouverGolfClub.ThishighpropertycrimeareaextendedalongAustinAvenuebetweenBlueMountainStreetandMarmontStreetanduptoKingAlbertAvenue.AsecondareawasthecommercialareabetweenKingEdwardStreetandSchoolhouseStreetalongLougheedHighway.ThefinalhighconcentrationareawaslocatedontheeastsideofNorthRoadbetweenAustinAvenueandRochesterAvenue.

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FIGURE9:PROPERTYCRIMEHOTSPOTSINCOQUITLAMIN2015

AsdemonstratedinTable15,virtuallyallofthevariableswereatleastmarginallysignificantinexplainingpropertycrimeinCoquitlam.Consistentwithmanyofthemunicipalitiesinthisstudy,byfar,medianhouseholdincomeprovidedthebiggesteffect.Theproportionsofindividualswithlessthanhighschooleducation,renters,andhousingrequiringmajorrepairswereallmostthantwiceashighinpropertycrimehotspotareaswhencomparedtotherestofthecity.Alsoquiteconsistentwerethestrongeffectoflevelsofunmarriedpersonsandresidentialmobility.Simplyput,therewereverylargestructuraldifferencesbetweenpropertycrimehotspotandnon-hotspotareasinCoquitlam.Ineffect,propertycrimehotspotareasweredistinctfromtheotherpartsofthecityacrossanumberofkeysocial,economic,andhousingmeasures.

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TABLE15:COMPARISONOFPROPERTYCRIMEHOTSPOTSANDNON-HOTSPOTS–COQUITLAM

Hotspots Non-Hotspots tvaluePopulationDensity 5,783 3,854 1.84*PopulationChange2006-2011(%) 39.5% 8.5% 1.24YoungMales-Aged15-24(%) 6.2% 7.7% -2.19**Unmarried(%) 52.5% 40.0% 4.85**Mobility-Last5Years(%) 60.3% 36.7% 4.79**Immigration(%) 48.2% 39.0% 1.96*AboriginalPopulation(%) 1.4% 1.4% 0.08MedianHouseholdIncome($) $42,594 $80,493 -8.58**UnemploymentRate 6.0 5.7 0.18LabourForceParticipation(%) 61.0% 68.1% -2.34**LessThanHighSchoolEducation(%) 8.8% 4.3% 2.52**Renters(%) 47.6% 19.3% 3.93**HousingCondition-MajorRepairs(%) 6.3% 3.0% 1.83**p<.10;**p<.05

PORTCOQUITLAM

In2015,PortCoquitlamhad2,946propertycrimesor8.1propertycrimesperday,resultinginPortCoquitlamranking13thoutofthe21jurisdictionsconsideredinthisreport.VerysimilartotheprofileforCoquitlampresentedabove,themostcommontypesofpropertycrimeinPortCoquitlamweretheftfromvehicle(34.0percent),mischieftoproperty(15.5percent),andotherunder$5000(10.0percent).Thiswasfollowedbyshoplifting(8.2percent),andautotheft(7.3percent).Intotal,thesefiveoffencetypescomprisedthree-quartersofallpropertycrimesinPortCoquitlamin2015.Onaverage,inatypicaldayin2015,theRCMPrecorded2.7theftsfromvehicles,1.2mischiefstoproperty,andlessthanoneothertheftunder$5,000andautotheftperday,inadditiontoalltheotheroffencetypespresentedinTable16.Intermsofthemoreseriouspropertycrimes,inadditiontothe214autotheftsin2015,therewerealso174breakandentersofabusiness,151breakandentersofaresidence,and45breakandenters‘other’.Takingallthebreakandenterstogether,theRCMPrecordedapproximatelyonebreakandenterperdayinPortCoquitlam.Finally,therewerealsoanumberofarsons(n=26)andasmallnumberofothertheftover$5,000(n=19).Ineffect,excludingthemoreserioustypesofpropertycrime,nearlyfour-fifths(78.6percent)ofallpropertycrimewasofamoreminornatureinPortCoquitlamin2015.

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TABLE16:PROPERTYCRIMEPROFILEFORPORTCOQUITLAMIN2015

RawNumber(n=2,946) %ofTotal

TheftFromVehicle 1,000 34.0%MischieftoProperty 455 15.5%OtherTheftUnder$5,000 293 10.0%Shoplifting 242 8.2%AutoTheft 214 7.3%Frauds 186 6.3%Break&Enter–Business 174 5.9%Break&Enter–Residence 151 5.1%BikeTheft 110 3.7%Break&Enter–Other 45 1.5%Arson 26 0.9%PossessionofStolenProperty 25 0.9%OtherTheftOver$5,000 19 0.6%

PropertycrimewasdistributedthroughoutPortCoquitlamin2015.AsdemonstratedbyFigure10,therewereanumberofhotspotclustersinPortCoquitlam.Morespecifically,thelargesthotspotinPortCoquitlamextendedtoboththeeastandwestsidesofShaughnessyStreetfromapproximatelyHawthorneAveinthesouthtotheareajustnorthofLougheedHighway.Infact,therewasahighconcentrationofpropertycrimeasfarwestasReeveStreetandPittRiverRoadtoGrantAvenueandYorkStreet.Ofnote,thislargeareaisamixofresidential,commercial,andindustrialareas.ThesecondmainhotspotinPortCoquitlamwasinthecenterofthecityintheareaspanningoutinalldirectionsfromtheintersectionofGrantAvenueandVincentStreettoeastofWellingtonStreetandeastofCoastMeridianRoad.Moreover,thishighconcentrationareaextendednorthofCoquitlamAvenuetoDorsetAvenue.Thisareaincludesamixofresidentialandcommercialzones.

Therewasanotherhighconcentrationareainthenorth-westofthecitywhereWestwoodStreetandLougheedHighwayintersected.Thisareaisalargeshoppingandcommercialarea.TherewerealsotwoemerginghotspotsjustsouthofDominionAvenueinthecommercialandshoppingareasaroundNicolaAvenue.Thesetwolocationsarecharacterizedbyseveralbigboxstores,othersmallerstores,andrestaurants,andtheyborderLougheedHighway.

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FIGURE10:PROPERTYCRIMEHOTSPOTSINPORTCOQUITLAMIN2015

Withtheexceptionsoftheunemploymentrate,labourforceparticipation,andproportionofresidentswhoself-identifiedasAboriginal,allofthestructuralvariablesweresignificantpredictorsofvariationsinneighborhoodpropertycrimeinPortCoquitlam(seeTable17).Themostnoteworthyindicatorswerethepercentageofunmarriedindividualsandresidentialmobility,bothofwhichweresignificantlyhigherinhotspotareaswhencomparedtotheotherareasofthecity.Ineffect,propertycrimehotspotsweresimilarlycharacterizedbyahigherproportionofrentersandtheproportionofhousinginpoorcondition.Moreover,propertycrimehotspotareashadelevatedlevelsofimmigration,andweremoredenselypopulated.Propertycrimehotspotareasalsohadsignificantlylowerincomelevels.Finally,theeffectsofpopulationchangeandhavingagreaterproportionofresidentswithlessthanhighschooleducation,whichweregreaterinhotspotareas,weremarginallysignificant.

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TABLE17:COMPARISONOFPROPERTYCRIMEHOTSPOTSANDNON-HOTSPOTS–PORTCOQUITLAM

Hotspots Non-Hotspots tvaluePopulationDensity 5,374 3,339 2.20**PopulationChange2006-2011(%) 20.7% 3.3% 1.79*YoungMales-Aged15-24(%) 6.2% 8.3% -4.45**Unmarried(%) 47.6% 38.5% 5.83**Mobility-Last5Years(%) 49.1% 30.6% 5.34**Immigration(%) 32.5% 25.4% 2.69**AboriginalPopulation(%) 3.9% 2.6% 0.93MedianHouseholdIncome($) $63,651 $86,109 -3.85**UnemploymentRate 4.4 4.8 -0.29LabourForceParticipation(%) 68.1% 71.4% -1.64LessThanHighSchoolEducation(%) 9.1% 6.4% 1.67*Renters(%) 30.2% 14.7% 3.61**HousingCondition-MajorRepairs(%) 6.5% 3.2% 2.08***p<.10;**p<.05

DELTA

In2015,Deltahad3,279propertycrimesorapproximatelyninepropertycrimesperday.Byvolume,Deltaranked12thoutofthe21jurisdictionsconsideredinthisreport.Verysimilartotheprofilespresentedabove,themostcommontypesofpropertycrimeweretheftfromvehicle(27.5percent),mischieftoproperty(18.0percent),andothertheftunder$5000(12.7percent).Thiswasfollowedbyfraud(9.2percent)andshoplifting(8.6percent).Intotal,thesefiveoffencetypescomprisedthree-quarters(76percent)ofallpropertycrimesinDeltain2015.Inatypicalday,onaverage,theDeltaPoliceDepartmentrecorded2.5theftsfromvehicles,1.6mischiefstoproperty,1.1othertheftsunder$5,000,andunderoneautotheftperday,inadditiontoalltheotheroffencetypespresentedinTable18.Intermsofthemoreseriouspropertycrimes,inadditiontothe233autotheftsin2015,therewerealso167breakandentersofaresidence,136breakandentersofabusiness,and59breakandenters‘other’.Takingallthebreakandenterstogether,theDeltaPoliceDepartmentrecorded,onaverage,approximatelyonebreakandenterperday.Finally,therewerealsoasmallnumberofarsons(n=15)andasmallnumberofothertheftover$5,000(n=34).Ineffect,excludingthemoreserioustypesofpropertycrime,four-fifths(80.2percent)ofallpropertycrimewasofamoreminornatureinDeltain2015.

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TABLE18:PROPERTYCRIMEPROFILEFORDELTAIN2015

RawNumber(n=3,279) %ofTotal

TheftFromVehicle 898 27.5%MischieftoProperty 586 18.0%OtherTheftUnder$5,000 415 12.7%Frauds 301 9.2%Shoplifting 279 8.6%AutoTheft 233 7.1%Break&Enter–Residence 167 5.1%Break&Enter–Business 136 4.2%BikeTheft 114 3.5%Break&Enter–Other 59 1.8%OtherTheftOver$5,000 34 1.0%PossessionofStolenProperty 23 0.7%Arson 15 0.5%

In2015,Deltahadthreemainareasofthecitywherepropertycrimesoccurredwithanydegreeofvolume;however,onlyoneofthemhadasubstantialhotspotforpropertycrime(seeFigure11).Thelargestconcentrationofpropertycrimeextendedfromthenorth-easternboundaryofDeltaalong120Streetto116Street.Here,thereweretwomainareasofconcentration.Oneareaofhighvolumeofpropertycrimeextendedfrom96Avenueto80Avenue,withahotspotbetween80Avenueand82Avenue,whilethesecondareaextendedaroundtheareawhere72Avenueand120Streetintersected,withanotherhotspotjusttothesouthof72Avenue.Theotherareaofhighconcentrationwaswhere84Avenueand112Streetintersected;namely,theareaaroundtheGeorgeMackieLibrary.

ThesecondmainareaofpropertycrimeconcentrationspreadoutfromthecommercialareaaroundtheintersectionofLadnerTrunkRoadand52aStreetinLadner.Thatareaismadeupoftwomainshoppingareas.ThefinalhotspotwastothesouthinTsawassenattheintersectionof56Streetand12Avenue.Again,thishotspotwaslocatedrightinthemiddleofanumberofstripmallsandoutdoorshoppinglocations.

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FIGURE11:PROPERTYCRIMEHOTSPOTSINDELTAIN2015

TheprofileofeffectsforDeltacloselyresembledthatfoundinCoquitlam.Onceagain,themostimportantpredictorofpropertycrimewasmedianhouseholdincome(seeTable19).Whiletheeffectsizesforrenters,proportionofresidentsnotmarried,residentialmobility,andlabourforceparticipationwereallsmallerinDeltathaninCoquitlam,theywerestillstatisticallysignificant.Theeffectoflessthanhighschooleducationwasalsoattenuated,butit,nonetheless,remainedmarginallystatisticallysignificant.Ofnote,theimmigrantpopulationinDeltawasabout25%largerinhotspotareascomparedtotherestofthecity.Infact,thevariablesthatmostdistinguishedDeltafromCoquitlamwerepopulationdensityandhousingcondition,bothofwhichweremarginallysignificantintheCoquitlammodel,butneitherofwhichwerestatisticallysignificantinDelta.

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TABLE19:COMPARISONOFPROPERTYCRIMEHOTSPOTSANDNON-HOTSPOTS–DELTA

Hotspots Non-Hotspots tvaluePopulationDensity 3,409 3,142 0.80PopulationChange2006-2011(%) 4.8% 3.2% 0.42YoungMales-Aged15-24(%) 6.3% 7.2% -2.06**Unmarried(%) 42.7% 36.1% 4.17**Mobility-Last5Years(%) 38.3% 30.7% 2.57**Immigration(%) 35.1% 27.6% 2.61**AboriginalPopulation(%) 1.8% 1.8% -0.04MedianHouseholdIncome($) $64,888 $88,985 -4.71**UnemploymentRate 5.6 4.7 0.74LabourForceParticipation(%) 60.2% 67.3% -3.33**LessThanHighSchoolEducation(%) 10.6% 6.9% 1.86*Renters(%) 24.3% 13.7% 2.49**HousingCondition-MajorRepairs(%) 4.0% 2.4% 1.15*p<.10;**p<.05

HOPE

In2015,thenumberofpropertycrimesinHopewaslowerthanintheothercitiesdiscussedinthisreport.Infact,byvolume,Hoperankedlastoutofthe21jurisdictionsconsideredinthisreportfortherawnumberofpropertycrimesrecordedbythepolice.Specifically,HopeRCMPrecorded565propertycrimeorapproximately1.5propertycrimesperday(seeTable20).Whileinaslightlydifferentorderthanthejurisdictionspreviouslydiscussed,thetopthreepropertycrimeswerethesameasinmostothercities;namely,mischieftoproperty(27.7percent),othertheftunder$5,000(19.5percent),andtheftfromvehicle(15.9percent).Whilethenumberofoffenceswasverylow,itisnoteworthythatthefourthmostcommonpropertycrimeinHopewasabreakandenterofabusiness.Infact,breakandentersofalltypesmadeup15.9%ofallpropertycrimesinHopein2015.Similartoothercitiesin2015,thelessseriouspropertycrimescomprised76.8%ofallpropertycrimeinHope.

TABLE20:PROPERTYCRIMEPROFILEFORHOPEIN2015

RawNumber(n=565) %ofTotal

MischieftoProperty 155 27.7%OtherTheftUnder$5,000 109 19.5%TheftFromVehicle 89 15.9%Break&Enter–Business 37 6.6%AutoTheft 32 5.7%Break&Enter–Residence 30 5.4%Frauds 25 4.5%BikeTheft 22 3.9%Break&Enter–Other 22 3.9%Shoplifting 22 3.9%PossessionofStolenProperty 8 1.4%Arson 5 0.9%OtherTheftOver$5,000 0 0

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GiventhegeographiclayoutofHope,itwasnotsurprisingthatpropertycrimeswereconcentratedinjusttwopartsofthecity.Evenso,therewasonemainhotspot,whichwassurroundedbyanotherareaofhighvolumeofpropertycrimecoveringmostofthecommercialshoppingareaincentralHope(seeFigure12).Morespecifically,themainhotspotwasfromaroundMemorialParkto6AvenueandfromParkStreettoFortStreet.ThesecondareawithaclusteringofpropertycrimewasfoundintheareaneartheSilverCreekElementarySchoolaroundFloodHopeRoad.

FIGURE12:PROPERTYCRIMEHOTSPOTSINHOPEIN2015

AsdemonstratedinTable21,onlytwovariableswereoutrightstatisticallysignificantindifferentiatingthepropertycrimehotspotfromthenon-hotspotareasinHope;namely,theproportionofresidentswhowereunmarriedandresidentialmobility.OthervariablesthathadamarginallysignificanteffectinpredictingpropertycrimeinHopeincludedpopulationchange,theproportionofrenters,andtheproportionofresidentswhoself-identifiedasAboriginal.Therestofthevariablesshowedverylittledifferencebetweenthepropertycrimehotspotareaandtheotherpartsofthecity.ItisimportanttonotethatHopehadthefewestnumberdisseminationareas(n=13).Withsuchasmallsample,itisdifficulttoreachstatisticalsignificance.ThisunderscoresthemagnitudeoftheeffectsproducedbytheunmarriedandmobilityindicatorsforHope.

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TABLE21:COMPARISONOFPROPERTYCRIMEHOTSPOTSANDNON-HOTSPOTS–HOPE

Hotspots Non-Hotspots tvaluePopulationDensity 1,068 666 0.66PopulationChange2006-2011(%) 3.3% -5.9% 2.09*YoungMales-Aged15-24(%) 4.3% 5.4% -1.17Unmarried(%) 59.2% 39.3% 12.38**Mobility-Last5Years(%) 57.6% 32.5% 2.41**Immigration(%) 11.3% 16.7% -0.60AboriginalPopulation(%) 15.9% 6.5% 2.04*MedianHouseholdIncome($) $32,714 $51,362 -1.92*UnemploymentRate 9.0 8.1 0.17LabourForceParticipation(%) 58.0% 51.6% 1.65LessThanHighSchoolEducation(%) 17.0% 12.3% 0.54Renters(%) 49.9% 16.6% 2.04*HousingCondition-MajorRepairs(%) 9.0% 4.4% 0.78*p<.10;**p<.05

LANGLEY

In2015,Langleyhad7,989propertycrimesor21.9propertycrimesperday.Byvolume,Langleyrankedfifthoutofthe21jurisdictionsconsideredinthisreport.Verysimilartotheprofilespresentedabove,themostcommontypesofpropertycrimerecordedbytheLangleyRCMPweretheftfromvehicle(23.3percent),othertheftunder$5000(15.6percent),andmischieftoproperty(13.4percent).Thiswasfollowedbyshoplifting(10.5percent)andautotheft(8.9percent).Intotal,thesefiveoffencetypescomprisedmorethantwo-thirds(71.7percent)ofallpropertycrimesinLangleyin2015.Inatypicalday,onaverage,LangleyRCMPrecorded5.1theftsfromvehicles,3.4othertheftsunder$5,000,2.9mischiefstoproperty,andapproximatelytwoautotheftsperday,inadditiontoalltheotheroffencetypespresentedinTable22.Intermsofthemoreseriouspropertycrimes,inadditiontothe708autotheftsin2015,therewerealso629breakandentersofabusiness,364breakandentersofaresidence,and170breakandenters‘other’.Takingallthebreakandenterstogether,LangleyRCMP,onaverage,recorded3.2breakandentersperday.Finally,therewerealso59arsons,andasmallnumberoftheftover$5,000(n=63).Ineffect,four-fifthsofallpropertycrimewasofamoreminornatureinLangleyin2015.

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TABLE22:PROPERTYCRIMEPROFILEFORLANGLEYIN2015

RawNumber(n=7,989) %ofTotal

TheftFromVehicle 1,856 23.3%OtherTheftUnder$5,000 1,244 15.6%MischieftoProperty 1,067 13.4%Shoplifting 841 10.5%AutoTheft 708 8.9%Frauds 714 8.9%Break&Enter–Business 629 7.9%Break&Enter–Residence 364 4.6%BikeTheft 181 2.3%Break&Enter–Other 170 2.1%PossessionofStolenProperty 82 1.0%OtherTheftOver$5,000 63 0.8%Arson 59 0.7%

WhilepropertycrimewasdistributedthroughoutLangley,asdemonstratedinFigure13,allofthemajorhotspotsforpropertycrimeinLangleywerelocatedinthewesternpartofthecityalongitsborderwithSurrey.ThelargesthotspotwascentralizedintheareaaroundtheCascadesCasinoneartheintersectionofGloverRoadandFraserHighway.OfnotethishighpropertycrimeareaextendedfromjustnorthofFraserHighwayto54Avenuebetween201aStreetand206Street.Thisareaisoverwhelminglycommercial.AsecondhotspotwasintheareajustnorthofwheretheLangleyBypassand196Streetintersect.Inadditiontothishotspot,thehighvolumeofpropertycrimeextendedtocovertheWillowbrookShoppingCentre.Afinalhighvolumeareawasjusttothenorth-eastoftheWillowbrookShoppingCentrealong64Avenuebetween200Streetand203Street.Infact,thehotspothereisagaininashoppingareamadeupofseverallargeboxstoressurroundedbysmallerstoresandshops.Itshouldbenotedthat,althoughthisareadidnothaveaconcentrationofpropertycrimetoregisterasahotspot,therewasalargeamountofpropertycrimeinthesoutheasternpartofthecity,namelyinAldergrovealongFraserHighwayand264StreetandalongFraserHighwayand272Street.

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FIGURE13:PROPERTYCRIMEHOTSPOTSINLANGLEYIN2015

AsdemonstratedinTable23,themostnotablepredictorofpropertycrimeinLangleywasthepercentageoftheareathatwascomprisedofrenters.Langleyhadoneofthelargestdifferentialsforrentersbetweenpropertycrimehotspotsandnon-hotspotareas.Specifically,thepropertycrimehotspothad2.8timesasmanyrentersasthenon-hotspotareasofthecity.Inaddition,propertycrimehotspotsinLangleyfeaturedsignificantlylowermedianhouseholdincomelevelsandhigherlevelsofresidentialmobility,whiledifferencesintheproportionofunmarriedpersonswhencomparingthepropertycrimehotspotareaswiththenon-hotspotareaswasmarginallystatisticallysignificant.

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TABLE23:COMPARISONOFPROPERTYCRIMEHOTSPOTSANDNON-HOTSPOTS–LANGLEY

Hotspots Non-Hotspots tvaluePopulationDensity 2,853 2,371 0.45PopulationChange2006-2011(%) 11.0% 5.6% 0.20YoungMales-Aged15-24(%) 3.5% 6.9% -3.90**Unmarried(%) 56.9% 39.0% 2.23*Mobility-Last5Years(%) 62.6% 39.2% 2.88**Immigration(%) 19.3% 16.5% 0.73AboriginalPopulation(%) 4.0% 3.0% 0.51MedianHouseholdIncome($) 45107 78090 -2.85**UnemploymentRate 4.5 4.6 -0.03LabourForceParticipation(%) 54.8% 69.8% -1.25LessThanHighSchoolEducation(%) 11.3% 8.2% 0.79Renters(%) 45.0% 15.9% 3.69**HousingCondition-MajorRepairs(%) 4.8% 1.8% 1.45*p<.10;**p<.05

MAPLERIDGE

Bythevolumeofpropertycrimein2015,MapleRidgerankedtenthoutofthe21jurisdictionsconsideredinthisreport.Therewere4,506propertycrimesinMapleRidgeor12.3propertycrimesperdayin2015.Asexpectedbasedontheprofilesalreadypresented,themostcommontypesofpropertycrimeinMapleRidgeweretheftfromvehicle(27.4percent),mischieftoproperty(19.5percent),andothertheftunder$5000(17.1percent).Thiswasfollowedbyshoplifting(7.6percent)andfraud(6.3percent).Intotal,thesefiveoffencetypescomprisedmorethanthree-quarters(77.9percent)ofallpropertycrimesin2015inMapleRidge(seeTable24).Inatypicaldayin2015,onaverage,theRCMPrecorded3.4theftsfromvehicles,2.4mischiefstoproperty,2.1othertheftsunder$5,000,andlessthanoneautotheftsperdayinMapleRidge,inadditiontoalltheotheroffencetypespresentedinTable24.Intermsofthemoreseriouspropertycrimes,inadditiontothe257autotheftsin2015,therewerealso222breakandentersofaresidence,196breakandentersofabusiness,and77breakandenters‘other’.Takingallthebreakandenterstogether,theRCMPreported,onaverage,1.4breakandentersperday.Finally,therewerealso31arsons,andasmallnumberoftheftover$5,000(n=42).Giventhis,slightlymorethanfour-fifths(81.7percent)ofallpropertycrimewasofamoreminornatureinMapleRidgein2015.

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TABLE24:PROPERTYCRIMEPROFILEFORMAPLERIDGEIN2015

RawNumber(n=4,506) %ofTotal

TheftFromVehicle 1,233 27.4%MischieftoProperty 878 19.5%OtherTheftUnder$5,000 768 17.1%Shoplifting 340 7.6%Frauds 282 6.3%AutoTheft 257 5.7%Break&Enter–Residence 222 4.9%Break&Enter–Business 196 4.4%BikeTheft 95 2.1%Break&Enter–Other 77 1.7%PossessionofStolenProperty 77 1.7%OtherTheftOver$5,000 42 0.9%Arson 31 0.7%

AsdemonstratedinFigure14,thevastmajorityofpropertycrimeinMapleRidgewasconcentratedinthesouth-westernpartofthecity.Therewasonesignificanthotspotzonein2015thatemanatedinalldirectionsfromtheintersectionofDewdneyTrunkRoadand224Street.Tothesouth,thishotspotextendedtoLougheedHighway,andnorthwardsto122Avenue.Thehotspotstretchedfrom222Streettojustpast228Street.Ofnote,thishotspotcoversbothresidentialandcommercialareas.Therewasasecond,smallhighconcentrationhotspotbetweenDewdneyTrunkRoadandLougheedHighwayalong203Street.Thiswasnotsurprisinggiventhatoneithersideof203Streetinthisareaarelargeshoppingareas.

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FIGURE14:PROPERTYCRIMEHOTSPOTSINMAPLERIDGEIN2015

AswasthecasewithLangley,thepercentageofrentershadthegreatesteffectonpropertycrimeinMapleRidge(seeTable25).Thepercentageofunmarriedpersonswasalsostronglyrelatedtopropertycrimerates,aswasresidentialmobilityandmedianhouseholdincome.Otherstatisticallysignificantdistinguishingcharacteristicsbetweenpropertycrimehotspotareasandnon-hotspotareasincludedhavingagreaterproportionofresidentswithlessthanahighschooleducationandhousingcondition,whilepopulationdensitywasonlymarginallysignificant.Conversely,neitheroftheeconomicindicators,namely,unemploymentrateandlabourforceparticipation,showedsignificantdifferencesbetweenhotspotandnon-hotspotareas;nordidthemeasuresfortheproportionofresidentswhowereAboriginal,theproportionofresidentswhowererecentimmigrants,oroverallpopulationchangeinMapleRidge.

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TABLE25:COMPARISONOFPROPERTYCRIMEHOTSPOTSANDNON-HOTSPOTS–MAPLERIDGE

Hotspots Non-Hotspots tvaluePopulationDensity 4,632 2,163 2.04*PopulationChange2006-2011(%) 11.7% 5.6% 0.53YoungMales-Aged15-24(%) 5.9% 7.5% -2.04**Unmarried(%) 64.6% 39.7% 9.88**Mobility-Last5Years(%) 61.2% 36.4% 4.27**Immigration(%) 17.6% 16.7% 0.35AboriginalPopulation(%) 3.4% 2.7% 0.49MedianHouseholdIncome($) $32,510 $78,041 -6.06**UnemploymentRate 7.8 5.2 1.28LabourForceParticipation(%) 57.2% 69.5% -1.61LessThanHighSchoolEducation(%) 16.6% 6.8% 3.59**Renters(%) 67.1% 12.4% 10.75**HousingCondition-MajorRepairs(%) 13.3% 2.2% 3.06***p<.10;**p<.05

MISSION

In2015,Missionhad2,804propertycrimesor7.7propertycrimesperday.Byvolumealone,Missionranked14thoutofthe21jurisdictionsconsideredinthisreport.Verysimilartotheprofilespresentedabove,themostcommontypesofpropertycrimeweretheftfromvehicle(25.8percent),mischieftoproperty(20.3percent),andothertheftunder$5000(13.9percent).Thiswasfollowedbyautotheft(8.8percent)andshoplifting(6.4percent).Intotal,thesefiveoffencetypescomprisedthree-quarters(75.2percent)ofallpropertycrimesinMissionin2015.Inatypicalday,onaverage,theMissionRCMPreportedtwotheftsfromvehicles,1.6mischiefstoproperty,1.1othertheftsunder$5,000,andjustunderoneautotheftperday,inadditiontoalltheotheroffencetypespresentedinTable26.Intermsofthemoreseriouspropertycrimes,inadditiontothe245autotheftsin2015,therewerealso163breakandentersofaresidence,101breakandentersofabusiness,and126breakandenters‘other’.Takingallthebreakandenterstogether,MissionRCMPrecordedapproximatelyonebreakandenterperday.Finally,therewerealsoanumberofarsons(n=19)andaverysmallnumberoftheftover$5,000(n=18).Ineffect,excludingthemoreserioustypesofpropertycrime,approximatelythree-quarters(76percent)ofallpropertycrimewasofamoreminornatureinMissionin2015.

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TABLE26:PROPERTYCRIMEPROFILEFORMISSIONIN2015

RawNumber(n=2,804) %ofTotal

TheftFromVehicle 722 25.8%MischieftoProperty 567 20.3%OtherTheftUnder$5,000 388 13.9%AutoTheft 245 8.8%Shoplifting 179 6.4%Break&Enter–Residence 163 5.8%Frauds 150 5.4%Break&Enter–Other 126 4.5%Break&Enter–Business 101 3.6%BikeTheft 67 2.4%PossessionofStolenProperty 51 1.8%Arson 19 0.7%OtherTheftOver$5,000 18 0.6%

Asexpected,muchofthepropertycrimeinMissionwasconcentratedinthesouthernpartofthecity(seeFigure15).ThereweretwoareasofhigherconcentrationofpropertycrimeinMissionin2015.Themainhotspotextendedfrom2ndAvenuefromCedarStreettoStaveLakeStreetandfromjustsouthofLougheedHighwaytojustsouthof7thAvenue.Thishotspotanditssurroundingareaofhighconcentrationofpropertycrimeischaracterizedbyamixofcommercialandresidentialblocks.ThesecondareaofhighvolumewastothewestofthemainhotspotandcenteredaroundanotherlargecommercialandindustrialareaalongLougheedHighwayandthetraintracks,borderedbytheAbbotsfordMissionHighwayandtheCedarValleyConnector.

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FIGURE15:PROPERTYCRIMEHOTSPOTSINMISSIONIN2015

AswasthecasewithHope,thepredictorthatexertedthegreatesteffectonthelevelsofpropertycrimeinMissionwasthepercentageofindividualswhowereunmarried.Aswithmostothermunicipalities,theproportionofrentersandthemedianhouseholdincomealsovariedsignificantlybetweenthepropertycrimehotspotareasandthenon-hotspotarea.Inaddition,asdemonstratedinTable27,thehotspotareasinMissionhadproportionatelymoreindividualswithlowereducationlevels.Finally,theprevalenceofpoorhousinginthepropertycrimehotspotareaswasmarginallystatisticallysignificant.

ItshouldbenotedthattheeffectsofsomevariablesinMissionwereintheanticipateddirection,butthemagnitudeoftheeffectsizedidnotreachtherequiredleveltobeconsideredstatisticallysignificant.Forexample,althoughresidentialmobilitywashigherinthepropertycrimehotspotareascomparedtotherestofthecity,Missionwasoneofthefewmunicipalitieswhereresidential

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mobilitywasnotrelatedtopropertycrimelevels.Similarly,populationdensityandthelevelsofimmigrationwerehigherandlowerrespectivelyinthepropertycrimehotspotareas,butnotstatisticallysignificantlyhigherorlower.Conversely,theeffectsofseveralothervariableswerecontrarytowhatwasexpected,buttheyalsofailedtoachievestatisticalsignificance.Forexample,populationchangewaslowerinthepropertycrimehotspotareas,whilelabourforceparticipationwashigherinthehotspotareascomparedtotherestofthecity.Again,althoughtheserelationshipswereunusual,theywerenotstatisticallysignificantinMission.

TABLE27:COMPARISONOFPROPERTYCRIMEHOTSPOTSANDNON-HOTSPOTS–MISSION

Hotspots Non-Hotspots tvaluePopulationDensity 2,145 1,868 0.39PopulationChange2006-2011(%) -1.2% 5.7% -0.45YoungMales-Aged15-24(%) 5.8% 7.2% -1.35Unmarried(%) 58.0% 41.2% 4.24**Mobility-Last5Years(%) 44.6% 37.5% 0.91Immigration(%) 8.6% 12.8% -0.92AboriginalPopulation(%) 10.1% 5.5% 1.15MedianHouseholdIncome($) $42,777 $71,087 -2.70**UnemploymentRate 4.7 4.3 0.10LabourForceParticipation(%) 70.3% 67.0% 0.62LessThanHighSchoolEducation(%) 26.8% 13.1% 2.63**Renters(%) 48.2% 14.7% 3.88**HousingCondition-MajorRepairs(%) 9.8% 2.6% 1.74**p<.10;**p<.05

NEWWESTMINSTER

Therewere3,493propertycrimesinNewWestminsterin2015or9.6propertycrimesperday.Bywayofcomparison,NewWestminsterranked11thoutofthe21jurisdictionsconsideredinthisreport.Asexpectedbasedontheprofilesalreadypresented,themostcommonpropertycrimewastheftfromvehicle(20.2percent);however,thiswasfollowedbyshoplifting(15.4percent)inNewWestminster.Thenextthreepropertycrimetypesweremischieftoproperty(15.3percent),othertheftunder$5000(14.9percent),andfraud(10.2percent).Intotal,thesefiveoffencetypescomprisedslightlymorethanthree-quarters(76percent)ofallpropertycrimesin2015inNewWestminster(seeTable28).Onaverage,inatypicaldayin2015,theNewWestminsterPoliceDepartmentrecorded1.9theftsfromvehicle,1.5shopliftingoffences,1.5mischieftopropertyoffences,andlessthanoneautotheftperday,inadditiontoalltheotheroffencetypespresentedinTable28.Intermsofthemoreseriouspropertycrimes,inadditiontothe255autotheftsin2015,therewerealso193breakandentersofabusiness,175breakandentersofaresidence,and60breakandenters‘other’.Takingallthebreakandenterstogether,theNewWestminsterPoliceDepartmentreported,onaverage,1.2breakandentersperday.Finally,therewerealsoasmallnumberofarsons(n=13),andanequallysmallnumberoftheftover$5,000(n=14).Ineffect,excludingthemoreserioustypesofpropertycrime,approximatelyfour-fifths(79.7percent)ofallpropertycrimewasofamoreminornatureinNewWestminsterin2015.

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TABLE28:PROPERTYCRIMEPROFILEFORNEWWESTMINSTERIN2015

RawNumber(n=3,493) %ofTotal

TheftFromVehicle 701 20.2%Shoplifting 533 15.4%MischieftoProperty 531 15.3%OtherTheftUnder$5,000 516 14.9%Frauds 353 10.2%AutoTheft 255 7.3%Break&Enter–Business 193 5.6%Break&Enter–Residence 175 5.0%BikeTheft 91 2.6%Break&Enter–Other 60 1.7%PossessionofStolenProperty 37 1.1%OtherTheftOver$5,000 14 0.4%Arson 13 0.4%

Whileinthemiddleofallthejurisdictionsincludedinthisreport,intermsoftheirvolumeofpropertycrime,NewWestminster’spatternwassomewhatdifferentfromtheothersinthatpropertycrimewasfoundnearlythroughouttheentirecityin2015.Still,therewasonemainhotspotandonehighconcentrationarea(seeFigure16).ThemainhotspotspreadoutfromtheintersectionofCarnarvonStreetandEighthStreettotheFraserRivertothesouth,RoyalAvenuetotheNorth,TenthStreettothewest,andSixthStreettotheeast.Thisareaisbothresidentialandcommercialandanareafrequentedbytourists.TheotherhighconcentrationofpropertycrimewasfoundtothenorthbetweenFifthStreetandEighthStreetandSeventhAvenueandFifthAvenue.Thisareaischaracterizedbysomeshopping,commercialbusinesses,restaurants,andcondominiums.

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FIGURE16:PROPERTYCRIMEHOTSPOTSINNEWWESTMINISTERIN2015

Therewererelativelyfewvariablesthatdistinguishedpropertycrimehotspotsandnon-hotspotareasinNewWestminster(seeTable29).Thevariablewiththelargesteffectsizewasactuallyhousingcondition.However,thiseffectwasactuallyintheoppositedirectionfromwhatwasobservedinmanyothermunicipalitiesinthisreport.InNewWestminsterpropertycrimehotspotareas,theproportionofhousingneedingmajorrepairswassignificantlylowerthanitwasinthenon-hotspotareas.But,theeffectsofseveralothernotablevariablesweremorestraightforward.Medianhouseholdincomewassubstantiallylowerinpropertycrimehotspotareas,whilepopulationdensityandthepercentageofunmarriedindividualsweresubstantiallyhigher.Finally,thedifferenceinresidentialmobilitylevelsbetweenthepropertycrimehotspotareas(higherresidentialmobility)andnon-hotspotareas(lowerresidentialmobility)wasmarginallystatisticallysignificantinNewWestminster.

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Therewerealsoseveralvariablesthatoperatedasexpected,butwerenotstatisticallysignificantintheireffects.Forexample,thepercentagesofrentersandindividualswithlessthanahighschooleducationwerehigherinthepropertycrimehotspotareas,andlabourforceparticipationwassimilarlylowerintheseareas.Ofnote,thesizeofthesedifferencewasnotstatisticallysignificant.Oneinsignificantvariablethatisworthnotingwaspopulationchange,whichwasmorethan5½timeshigherinthepropertycrimehotspotareaswhencomparedtotherestofNewWestminster.Onthefaceofit,thisisamassivedifference.However,consistentwithsomeoftheothermunicipalitiesexaminedinthisreport,suchasAbbotsford,Burnaby,andMapleRidge,becauseofthewaythisstatisticaltestworks,thisapparentlylargevariationwasnotstatisticallysignificant.

TABLE29:COMPARISONOFPROPERTYCRIMEHOTSPOTSANDNON-HOTSPOTS–NEWWESTMINSTER

Hotspots Non-Hotspots tvaluePopulationDensity 13,674 6,929 2.87**PopulationChange2006-2011(%) 49.1% 6.4% 1.16YoungMales-Aged15-24(%) 5.4% 5.9% -0.38Unmarried(%) 57.9% 47.5% 2.37**Mobility-Last5Years(%) 59.2% 47.1% 1.74*Immigration(%) 37.3% 31.0% 1.24AboriginalPopulation(%) 1.3% 3.1% -1.82MedianHouseholdIncome($) $40,241 $64,322 -2.31**UnemploymentRate 9.2 7.4 0.55LabourForceParticipation(%) 59.8% 71.5% -1.73LessThanHighSchoolEducation(%) 9.5% 7.1% 0.79Renters(%) 52.2% 42.1% 0.87HousingCondition-MajorRepairs(%) 2.9% 7.7% -4.11***p<.10;**p<.05

NORTHVANCOUVER

In2015,NorthVancouverhad4,599propertycrimesorapproximately12.6propertycrimesperday.Justbyvolume,NorthVancouverrankedninthoutofthe21jurisdictionsconsideredinthisreport.Themostcommontypesofpropertycrimeweretheftfromvehicle(25.9percent),mischieftoproperty(21.6percent),andothertheftunder$5000(10.2percent).Thiswasfollowedbyfrauds(8.9percent)andshoplifting(8.8percent).Onaverage,inatypicalday,theNorthVancouverRCMPrecorded3.3theftsfromvehicles,2.7mischiefstoproperty,1.3othertheftunder$5,000,andapproximatelyoneautothefteverytwodays,inadditiontoalltheotheroffencetypespresentedinTable30.Intermsofthemoreseriouspropertycrimes,whiletherewere169autotheftsin2015,therewerealso307breakandentersofabusiness,233breakandentersofaresidence,and74breakandenters‘other’.Combiningallthedifferenttypesofbreakandenters,NorthVancouverRCMPrecorded1.7breakandentersperday.Finally,therewerealsoanumberofarsons(n=22)andasmallnumberoftheftsover$5,000(n=17)in2015.Insum,slightlymorethanfour-fifths(82.1percent)ofallpropertycrimewasofamoreminornatureinNorthVancouverin2015.

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TABLE30:PROPERTYCRIMEPROFILEFORNORTHVANCOUVER2015

RawNumber(n=4,599) %ofTotal

TheftFromVehicle 1,189 25.9%MischieftoProperty 990 21.6%OtherTheftUnder$5,000 470 10.2%Frauds 408 8.9%Shoplifting 402 8.8%Break&Enter–Business 307 6.7%BikeTheft 267 5.8%Break&Enter–Residence 233 5.1%AutoTheft 169 3.7%Break&Enter–Other 74 1.6%PossessionofStolenProperty 40 0.9%Arson 22 0.5%OtherTheftOver$5,000 17 0.4%

GiventhedistributionofresidentialandcommercialareasinNorthVancouver,itwasnotsurprisingthatthemajorityofpropertycrimeoccurredinthewesternandsouthernpartsofthecity.AsdemonstratedinFigure17,therewerethreeareaswithveryhighconcentrationsofpropertycrime.ThefirsthotspotemanatedfromMarineDrivebetweenHamiltonAvenueandFellAvenue.Asusual,therewasahighdensityzonethatsurroundedthishotspot.Thisareaischaracterizedmainlybyretailstores,stripmalls,andanoutdoormall.ThelargesthotspotwasfoundinLowerLonsdale,justtothenorth-eastoftheLonsdaleQuayMarket.Specifically,theareabetweenLonsdaleAvenueandSt.GeorgesAvenuebetween3rdStreetEastandthepiers.Thispartofthecityisamixofresidentialandcommercialareas.TherewasathirdareawithaveryspecifichotspotcenteredintheareabetweentheLionsGateHospitaland,interestingly,theNorthVancouverRCMPdepartmentbuilding.TheareaofhighconcentrationextendedfromLionsgateAvenuetoSt.AndrewsAvenueandbetween11thStreetEastto18thStreetEast.

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FIGURE17:PROPERTYCRIMEHOTSPOTSINNORTHVANCOUVERIN2015

AsdemonstratedinTable31,severalvariableswerestronglyassociatedwithdifferencesinpropertycrimelevelsacrossNorthVancouver.Themostnotableeffectwasinrelationtomedianhouseholdincome,whichwasabout80%higherinnon-hotspotpropertycrimeareas.HotspotsinNorthVancouverhadpopulationdensitiesthatwere3½timesgreaterthanthosefoundinthenon-hotspotareasofthecity.Hotspotareasalsohadsignificantlyhigherlevelsofrenters,unmarriedpersons,andresidentialmobility.Finally,propertycrimehotspotareaswerealsocharacterizedbyelevatedimmigrationrates.Formostoftheremainingvariables,thedifferencesbetweenhotspotandnon-hotspotareasinNorthVancouverwerenegligibleanddidnotrisetothelevelofstatisticalsignificance.

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TABLE31:COMPARISONOFPROPERTYCRIMEHOTSPOTSANDNON-HOTSPOTS–NORTHVANCOUVER

Hotspots Non-Hotspots tvaluePopulationDensity 14,094 3,900 8.09**PopulationChange2006-2011(%) 14.0% 2.5% 1.31YoungMales-Aged15-24(%) 4.4% 6.7% -5.73**Unmarried(%) 55.4% 40.7% 7.90**Mobility-Last5Years(%) 56.4% 36.0% 5.75**Immigration(%) 41.3% 31.8% 3.41**AboriginalPopulation(%) 1.4% 0.8% 1.10MedianHouseholdIncome($) $48,808 $87,543 -10.78**UnemploymentRate 5.5 4.2 1.03LabourForceParticipation(%) 69.4% 68.5% 0.23LessThanHighSchoolEducation(%) 3.3% 1.8% 1.35Renters(%) 53.2% 23.0% 5.59**HousingCondition-MajorRepairs(%) 5.7% 4.4% 0.77*p<.10;**p<.05

PITTMEADOWS

PittMeadowsranked17thoutofthe21jurisdictionsconsideredinthisreportintermsoftherawnumberofpropertyoffencesrecordedbythepolice,in2015,andhad1,001propertycrimesorapproximatelyjust2.7propertycrimesperday.Themostcommontypesofpropertycrimeweretheftfromvehicle(28.1percent),mischieftoproperty(19.5percent),andothertheftunder$5000(14.7percent).Thiswasfollowedbyshoplifting(13.6percent)andfrauds(6.5percent).Giventhis,onaverage,inatypicalday,thePittMeadowsRCMPrecordedlessthanonetheftfromvehicles,onemischieftoproperty,andoneothertheftunder$5,000everyotherday,inadditiontoalltheotheroffencetypespresentedinTable32.Intermsofthemoreseriouspropertycrimes,therewere56autotheftsin2015,36breakandentersofaresidence,32breakandentersofabusiness,and13breakandenters‘other’.Combiningallthedifferenttypesofbreakandenters,PittMeadowsRCMPrecordedonebreakandenterevery4½days.Therewerealsoveryfewarsons(n=6)andtheftsover$5,000(n=6)in2015.Overall,whilethenumberofpropertycrimeswaslow,85%ofallpropertycrimewasofamoreminornatureinPittMeadowsin2015.

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TABLE32:PROPERTYCRIMEPROFILEFORPITTMEADOWSIN2015

RawNumber(n=1,001) %ofTotal

TheftFromVehicle 281 28.1%MischieftoProperty 195 19.5%OtherTheftUnder$5,000 147 14.7%Shoplifting 136 13.6%Frauds 65 6.5%AutoTheft 56 5.6%Break&Enter–Residence 36 3.6%Break&Enter–Business 32 3.2%BikeTheft 17 1.7%Break&Enter–Other 13 1.3%PossessionofStolenProperty 9 0.9%Arson 6 0.6%OtherTheftOver$5,000 6 0.6%

AsdemonstratedinFigure18,virtuallyallofthepropertycrimeinPittMeadowsoccurredinthesouthernpartofthecityandwasfoundalongLougheedHighwayinamainlyresidentialarea.JustalongtheeasternedgeofthehotspotanditssurroundinghighvolumeareaistheoutdoorMeadowtownShoppingCentre,whichcontributedtomakingthistheareaofhighestconcentrationofpropertycrime.

FIGURE18:PROPERTYCRIMEHOTSPOTSINPITTMEADOWSIN2015

AsdemonstratedbyTable33,PittMeadowsisoneofthreemunicipalities,alongwithWestVancouverandWhistler,wherenoneofthestructuralindicatorsutilizedinthisstudywere

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substantiallyrelatedtopropertycrime.Simplyput,inmostcases,thevariationbetweenpropertycrimehotspotandnon-hotspotareasweregenerallyverysmall.Thedifferencesintermsoftheproportionofyoungmales,unmarriedresidents,immigration,Aboriginalpopulation,unemploymentrate,labourforceparticipation,proportionofresidentswithlessthanhighschooleducation,proportionofpeoplewhoarerenters,andhousingconditionwerealllessthanfivepercentagepoints,whilethedifferenceforresidentialmobilitydidnotexceedsixpoints.Putanotherway,intermsoftheircompositions,propertycrimehotspotsinPittMeadowslookedverymuchthesameasthenon-hotspotareasofthecity.ItispossiblethatthesefindingsweretheresultoftheoveralllowlevelofpropertycrimeinPittMeadows,whichmightsuppressthedetectionofanydifferencesbetweenthehotspotandthenon-hotspotareasofthecity.

TABLE33:COMPARISONOFPROPERTYCRIMEHOTSPOTSANDNON-HOTSPOTS–PITTMEADOWS

Hotspots Non-Hotspots tvaluePopulationDensity 1,087 3,309 -1.14PopulationChange2006-2011(%) 41.3% 9.4% 1.45YoungMales-Aged15-24(%) 6.3% 6.3% 0.05Unmarried(%) 36.7% 38.5% -0.31Mobility-Last5Years(%) 45.1% 39.3% 0.49Immigration(%) 25.9% 21.5% 0.77AboriginalPopulation(%) 2.3% 4.1% -0.50MedianHouseholdIncome($) $72,770 $73,963 -0.08UnemploymentRate 5.2 4.2 0.31LabourForceParticipation(%) 73.9% 69.6% 0.62LessThanHighSchoolEducation(%) 7.3% 3.7% 1.07Renters(%) 19.5% 18.3% 0.09HousingCondition-MajorRepairs(%) 3.6% 2.1% 0.37*p<.10;**p<.05

PORTMOODY

SimilartoPittMeadows,PortMoodyrankedfourthfromlastoutofthe21jurisdictionsconsideredinthisreportintermsoftherawnumberofpropertyoffencesrecordedbythepolicein2015.Thisaccountedfor904propertycrimesorapproximatelyjust2.5propertycrimesperday.Similartotheotherjurisdictions,themostcommontypesofpropertycrimeweretheftfromvehicle(35.4percent),mischieftoproperty(18.0percent),andothertheftunder$5000(12.9percent).Thiswasfollowedbyfrauds(11.2percent)andshoplifting(6.7percent).Giventhis,onaverage,inatypicalday,thePortMoodyPoliceDepartmentrecordedslightlylessthanonetheftfromvehicleperday,onemischieftopropertyeverytwodays,andoneothertheftunder$5,000everythirdday(seeTable34).Intermsofthemoreseriouspropertycrimes,therewere32autotheftsin2015,39breakandentersofaresidence,27breakandentersofabusiness,andsixbreakandenters‘other’.Combiningallthedifferenttypesofbreakandenters,thePortMoodyPoliceDepartmentrecordedonebreakandentereveryfivedays.Therewerealsoveryfewarsons(n=3)andtheftsover$5,000(n=8)in2015.Overall,thenumberofpropertycrimeswaslowand,whenexcludingthemore

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serioustypesofpropertycrime,87.2%ofallpropertycrimewasofamoreminornatureinPortMoodyin2015.

TABLE34:PROPERTYCRIMEPROFILEFORPORTMOODYIN2015

RawNumber(n=904) %ofTotal

TheftFromVehicle 318 35.4%MischieftoProperty 162 18.0%OtherTheftUnder$5,000 116 12.9%Frauds 101 11.2%Shoplifting 60 6.7%Break&Enter–Residence 39 4.3%AutoTheft 32 3.6%Break&Enter–Business 27 3.0%PossessionofStolenProperty 14 1.6%BikeTheft 13 1.4%OtherTheftOver$5,000 8 0.9%Break&Enter–Other 6 0.7%Arson 3 0.3%

Whilethedistributionofpropertycrimewasthroughoutthesouthernandeasternpartsofthecity,therewasonlyonemainhotspotinPortMoodyin2015.AsdemonstratedinFigure19,thecentreofthehotspotwasneartheintersectionofGuildfordWayandIocoRoad.ThehotspotextendednorthofGuildfordWaytoincludeshoppingareasandsomeresidentialneighbourhoods,includingthePortMoodyRecreationComplextoUnglessWay.ThehotspotalsoextendedtothesouthofGuildfordWaytoincludeanothersmallshoppingareatothewestofIocoRoadandaresidentialneighbourhoodtotheeastofIocoRoad.ThehighconcentrationofpropertycrimesalsoextendedalongbothsidesofBarnetHighwayandSt.JohnsStreettoincludeanothercommercialandresidentialarea.

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FIGURE19:PROPERTYCRIMEHOTSPOTSINPORTMOODYIN2015

Comparedwithmanyoftheothermunicipalitiesinthisstudy,theexplanationforthevariationsfoundinthedistributionofpropertycrimehotspotsinPortMoodyisverystraightforward.Thedifferencebetweenpropertycrimehotspotsandnon-hotspotswasprimarilydrivenbydifferencesinresidentialmobility,whichwasmuchhigherinthehotspotanditssurroundingarea,andthemedianhouseholdincome,whichwassignificantlylowerinthehotspotandsurroundinghighvolumearea(seeTable35).Inaddition,thepositiveeffectofpopulationdensitywasmarginallystatisticallysignificant.Theeffectoflabourforceparticipationsimilarlywasmarginallysignificant,butwascontrarytoexpectations,asitwasactuallyhigherinthehotspotandhighconcentrationarea.Manyoftheotherrelationships,includingthosefortheproportionofresidentswithlessthanhighschooleducation,theproportionofrenters,andpoorhousingcondition,wereinthepredicteddirection,butwerenotlargeenoughtobestatisticallysignificant.

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TABLE35:COMPARISONOFPROPERTYCRIMEHOTSPOTSANDNON-HOTSPOTS–PORTMOODY

Hotspots Non-Hotspots tvaluePopulationDensity 6,938 2,949 2.16*PopulationChange2006-2011(%) -1.8% 3.7% -0.45YoungMales-Aged15-24(%) 5.1% 7.3% -3.28**Unmarried(%) 42.6% 38.0% 1.41Mobility-Last5Years(%) 64.1% 36.4% 4.55**Immigration(%) 29.3% 27.4% 0.30AboriginalPopulation(%) 1.1% 2.9% -0.97MedianHouseholdIncome($) $65,866 $85,845 -3.43**UnemploymentRate 6.0 6.2 -0.10LabourForceParticipation(%) 77.3% 70.5% 1.78*LessThanHighSchoolEducation(%) 3.1% 2.8% 0.09Renters(%) 24.1% 22.9% 0.10HousingCondition-MajorRepairs(%) 12.5% 4.0% 1.10*p<.10;**p<.05

RICHMOND

In2015,Richmondhad8,237propertycrimesor22.6propertycrimesperday.Justbyvolume,Richmondrankedfourthoutofthe21jurisdictionsconsideredinthisreport.Themostcommontypesofpropertycrimeweretheftfromvehicle(28.8percent),othertheftunder$5000(15.9percent),andmischieftoproperty(16.6percent).Thiswasfollowedbyfraud(9.1percent)and,unlikemostoftheothercitiesexaminedthusfar,residentialbreakandenters(8.1percent).Ineffect,onaverage,inatypicalday,theRichmondRCMPrecorded6.5theftsfromvehicles,3.6othertheftunder$5,000,2.7mischiefstoproperty,andoneautotheft,inadditiontoalltheotheroffencetypespresentedinTable36.Intermsofthemoreseriouspropertycrimes,whiletherewere372autotheftsin2015,therewerealso670breakandentersofaresidence,381breakandentersofabusiness,and110breakandenters‘other’.Combiningallthedifferenttypesofbreakandenters,theRichmondRCMPrecorded3.2breakandentersperday.Finally,therewerealsoalargenumberofarsons(n=58)andasubstantialnumberoftheftsover$5,000(n=144).Insum,nearlyfour-fifths(78.6percent)ofallpropertycrimewasofamoreminornatureinRichmondin2015.

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TABLE36:PROPERTYCRIMEPROFILEFORRICHMONDIN2015

RawNumber(n=8,237) %ofTotal

TheftFromVehicle 2,367 28.8%OtherTheftUnder$5,000 1,310 15.9%MischieftoProperty 975 11.8%Frauds 745 9.1%Break&Enter–Residence 670 8.1%Shoplifting 668 8.1%Break&Enter–Business 381 4.6%AutoTheft 372 4.5%BikeTheft 312 3.8%OtherTheftOver$5,000 144 1.7%Break&Enter–Other 110 1.3%PossessionofStolenProperty 87 1.1%Arson 58 0.7%

InRichmond,mostofthepropertycrimewasrecordedinthewesternpartofthecity.AsdemonstratedinFigure20,thereweretwomainpocketsofhighconcentrationandonemajorhotspot.ThemainhotspotwasfoundinCityCenter,withthedensestareasforpropertyoffencesbeingfoundintheBrighouseVillageneighbourhoodbetweenWestminsterHighwayandGranvilleAvenuealongNo.3Road.Whilenotahotspot,therewasalsoahighconcentrationofpropertycrimecontinuingalongNo.3RoadtothenorthbetweenAlderbridgeWayandCambieRoad,anareaknownasAberdeenVillage.Whilethereareresidentialblocksinthisarea,thisisaverycommercialpartofthecity.ThesecondlargeconcentrationofpropertycrimewaslocatedattheVancouverInternationalAirport.

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FIGURE20:PROPERTYCRIMEHOTSPOTSINRICHMONDIN2015

ThepatternofresultsforRichmondwasreflectivewhathasbeennotedinmanyoftheotherlargermunicipalitiesinthisreport.AkintotheresultsfoundinAbbotsford,Burnaby,andSurrey,medianhouseholdincomewasthemostimportantpredictorofvariationsinpropertycrimeacrosshotspotandnon-hotspotareas(seeTable37).Proportionately,thedifferenceinincomeintheseareaswasamongthehighest(220%)ofallthemunicipalitiessurveyedhere.Aswell,theeffectofimmigration,whichwassignificantlygreaterinthepropertycrimehotspotandhighvolumeareas,wasthelargestsucheffectacrossallofthemunicipalities.Manyoftheremainingsignificantvariablesmightbecharacterizedasthe“usualsuspects.”Theproportionofrentersandunmarriedpersons,andlevelsofresidentialmobility,wereallelevatedintheRichmondpropertycrimehotspotandhighvolumearea,whichalsofeaturedsubstantiallyhigherpopulationdensities.ItisworthnotingthatlabourforceparticipationwassignificantlylowerinRichmond’spropertycrimehotspotandhighvolumeareascomparedtotheotherpartsofthecity.

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TABLE37:COMPARISONOFPROPERTYCRIMEHOTSPOTSANDNON-HOTSPOTS–RICHMOND

Hotspots Non-Hotspots tvaluePopulationDensity 15,403 5,017 2.93**PopulationChange2006-2011(%) 32.9% 8.0 1.12YoungMales-Aged15-24(%) 6.2% 7.4 -1.55Unmarried(%) 45.5% 39.5 3.10**Mobility-Last5Years(%) 57.8% 40.0 3.08**Immigration(%) 75.3% 57.2 9.41**AboriginalPopulation(%) 0.0% 0.5 -0.53MedianHouseholdIncome($) $30,902 $69,832 -16.20**UnemploymentRate 3.1 5.6 -1.20LabourForceParticipation(%) 51.7% 61.6% -2.57**LessThanHighSchoolEducation(%) 11.1% 6.7% 1.77*Renters(%) 39.8% 17.0% 3.09**HousingCondition-MajorRepairs(%) 2.9% 4.0% -0.38*p<.10;**p<.05

SQUAMISH

Squamishrankedthirdfromlastoutofthe21jurisdictionsconsideredinthisreportintermsoftherawnumberofpropertyoffencesrecordedbythepolicein2015.Thisaccountedfor753propertycrimesorapproximatelyjust2.1propertycrimesperday.Ofnote,themostcommontypeofpropertycrimeinSquamishwasmischieftoproperty(20.5percent)followedbytheftfromvehicle(20.1percent),andothertheftunder$5000(15.9percent).RoundingoutthetopfiveinSquamishwerefrauds(10.7percent)andautotheft(6.5percent)(seeTable38).Intermsofthemoreseriouspropertycrimes,therewere49autothefts,47breakandentersofaresidence,48breakandentersofabusiness,and11breakandenters‘other’in2015.Combiningallthedifferenttypesofbreakandenters,theSquamishRCMPrecordedapproximatelyonebreakandenterevery3½days.Therewerealsoveryfewarsons(n=5)andonlytwotheftsover$5,000in2015.Overall,whilethenumberofpropertycrimeswasverylowcomparedtootherjurisdictionsexaminedinthisreport,whenexcludingthemoreserioustypesofpropertycrime,morethanthree-quarters(78.4percent)ofallpropertycrimewasofamoreminornatureinSquamishin2015.

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TABLE38:PROPERTYCRIMEPROFILEFORSQUAMISHIN2015

RawNumber(n=753) %ofTotal

MischieftoProperty 154 20.5%TheftFromVehicle 151 20.1%OtherTheftUnder$5,000 119 15.9%Frauds 80 10.7%AutoTheft 49 6.5%Break&Enter–Business 48 6.4%Break&Enter–Residence 47 6.3%BikeTheft 37 4.9%Shoplifting 30 4.0%PossessionofStolenProperty 17 2.3%Break&Enter–Other 11 1.5%Arson 5 0.7%OtherTheftOver$5,000 2 0.3%

AlthoughtherewasverylittlepropertycrimeinSquamishin2015,asdemonstratedinFigure21,geographically,therewasonemajorhotspotinthesouthernpartofthecityandoneotherareaofhighconcentrationinthemiddleofthecity.ThehotspotinthesouthernpartofSquamishwascenteredattheintersectionofWinnipegStreetand2AvenueandextendedfromtheLoggersLaneto5AvenueandfromVictoriaStreettoBaileyStreet.Asexpected,thisisacommercialareawithanumberofhotelsandsomeresidences.ThehighconcentrationareawasalongtheSeatoSkyHighwaybetweenMamquamRoadandCheakamusWay.Again,thisareaisoverwhelminglycommercialwithanopenshoppingmallandothercommercialbusinesses.

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FIGURE21:PROPERTYCRIMEHOTSPOTSINSQUAMISHIN2015

Squamishcomesclosetobeingthe“prototypical”municipalitywithregardtoexplainingpropertycrime.Aswillbecomeevidentlater,therewerefourvariablesthatstoodoutinallofthemunicipal-levelanalysis;lowerlevelsofmedianhouseholdincome,higherlevelsofrenters,theproportionofunmarriedindividuals,andresidentialmobility(seeTable39).ThesewerepreciselytheeffectsfoundinSquamish,wherethesesamevariablesareallstatisticallysignificant.Additionally,increasedpopulationdensityanddecreasedproportionsofhighschoolgraduatesweremarginallysignificant.Theremainingvariableswereverysimilaracrossboththepropertycrimehotspotandtheotherareasofthecity,and,therefore,cannotdistinguishthehotspotfromthenon-hotspotareas.

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TABLE39:COMPARISONOFPROPERTYCRIMEHOTSPOTSANDNON-HOTSPOTS–SQUAMISH

Hotspots Non-Hotspots tvaluePopulationDensity 2,415 1,186 1.89*PopulationChange2006-2011(%) 17.1% 13.1% 0.42YoungMales-Aged15-24(%) 6.2% 6.2% 0.02Unmarried(%) 49.0% 36.5% 3.37**Mobility-Last5Years(%) 70.4% 45.9% 3.16**Immigration(%) 18.2% 16.6% 0.34AboriginalPopulation(%) 4.5% 3.3% 0.51MedianHouseholdIncome($) $53,448 $81,070 -2.08**UnemploymentRate 7.5 6.0 0.46LabourForceParticipation(%) 79.0% 76.0% 0.73LessThanHighSchoolEducation(%) 2.0% 7.1% -1.87*Renters(%) 50.1% 18.9% 2.70**HousingCondition-MajorRepairs(%) 10.7% 3.2% 1.13*p<.10;**p<.05

WHISTLER

Whistlerhadthesecondfewernumberofpropertycrimesamongthe21jurisdictionsconsideredinthisreport.AsdemonstratedinTable40,intermsoftherawnumberofpropertyoffencesrecordedbythepolice,in2015,Whistlerhad740propertycrimesorapproximatelyjusttwopropertycrimesperday.GiventhatWhistlerisprimarilyaseasonalvacationlocationwithasmallpermanentpopulation,itwasnotsurprisingthatthemostcommontypeofpropertyoffencewasothertheftunder$5,000(27.7percent),followedbymischieftoproperty(25.0percent),andtheftfromvehicle(11.6percent).Roundingoutthetopfivewerebiketheft(13.1percent)andfraud(5.2percent).Intermsofthemoreseriouspropertycrimes,therewerejust12autotheftsin2015,and23breakandentersofaresidence,11breakandentersofabusiness,and9breakandenters‘other’.Combiningallthedifferenttypesofbreakandenters,theRCMPrecordedonebreakandenterapproximatelyeveryeightdays.TherewasalsoonlyonearsonrecordedbytheRCMPandjust10theftsover$5,000in2015.Overall,inadditionaltothenumberofpropertycrimesbeingverylowinWhistlerin2015,87.2%ofallpropertycrimewasofamoreminornature.

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TABLE40:PROPERTYCRIMEPROFILEFORWHISTLERIN2015

RawNumber(n=740) %ofTotal

OtherTheftUnder$5,000 203 27.7%MischieftoProperty 183 25.0%TheftFromVehicle 85 11.6%BikeTheft 83 13.1%Frauds 38 5.2%Break&Enter–Residence 23 3.1%Shoplifting 22 3.0%AutoTheft 12 1.6%PossessionofStolenProperty 12 1.6%Break&Enter–Business 11 1.5%OtherTheftOver$5,000 10 1.4%Break&Enter–Other 9 1.2%Arson 1 0.1%

AsdemonstratedinFigure22,virtuallyallofthepropertycrimeinWhistleroccurredinthepartofthecityknownastheVillagebetweentheSea-To-SkyHighwayandBlackcombWay.ThiswasnotunexpectedasthisisthemaintouristandrecreationalareaofWhistlercharacterizedbyrestaurants,shoppingstores,bars,hotels,andparkinglots.

FIGURE22:PROPERTYCRIMEHOTSPOTSINWHISTLERIN2015

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WhistlerwassimilartoPittMeadowsandWestVancouverinsofarasitdidnotdemonstrateanystatisticallysignificantdifferencesbetweenitspropertycrimehotspotsandhighvolumeareas,anditsnon-hotspotareas.UnlikePittMeadowsandWestVancouver,however,thisfindingwaslessaboutalackofvariationandmoreaboutsamplesize.TherewereseveralvariablesthatshowedatleastmoderatesizeddifferencesbetweenWhistler’sonepropertycrimehotspotandtherestofthecity(seeTable41).Forexample,boththeproportionofunmarriedpeopleandresidencemobilityweremorethan10percentagepointshigherintheWhistlerhotspot,whichalsohadtwiceasmanyrenters.Atthesametime,theWhistlerhotspothadlessthanone-thirdtheproportionofimmigrants.But,becauseoftherelativelysmallnumberofdisseminationsareasinWhistler(n=17),noneofthesedifferenceswerestatisticallysignificant.

TABLE41:COMPARISONOFPROPERTYCRIMEHOTSPOTSANDNON-HOTSPOTS–WHISTLER

Hotspots Non-Hotspots tvaluePopulationDensity 402 611 -0.38PopulationChange2006-2011(%) 7.0% -2.3% 0.58YoungMales-Aged15-24(%) 8.8% 8.1% 0.27Unmarried(%) 57.4% 46.5% 1.44Mobility-Last5Years(%) 73.3% 62.3% 1.09Immigration(%) 5.3% 19.7% -1.70AboriginalPopulation(%) 0.0% 0.0% MedianHouseholdIncome($) $61,987 $67,133 -0.28UnemploymentRate 0.0 7.0 -1.20LabourForceParticipation(%) 87.3% 82.4% 0.60LessThanHighSchoolEducation(%) 0.0% 0.0% Renters(%) 63.3% 31.7% 1.54HousingCondition-MajorRepairs(%) 0.0% 0.3% -0.24*p<.10;**p<.05

SURREY

TheCityofSurreyhadthesecondhighestvolumeofpropertycrimein2015amongthe21jurisdictionsanalysedinthisreport.In2015,Surreyhad30,727propertycrimesorapproximately84propertycrimesperday.Althoughithadthesecondhighestnumberofpropertycrimes,thedistributionbytypeoftheseoffenceswasverysimilartomostoftheotherjurisdictions.Forexample,themostcommonpropertycrimeinSurreywastheftfromvehicle(23.5percent).Thiswasfollowedbyothertheftunder$5000(15.2percent),andmischieftoproperty(13.8percent).Roundingoutthetopfivepropertyoffencetypeswerefraud(12.1percent)andautotheft(10.4percent).Onaverage,inatypicalday,theSurreyRCMPrecorded19.8theftsfromvehicles,11.6mischiefstoproperty,12.8othertheftunder$5,000,and8.7autothefts,inadditiontoalltheotheroffencetypespresentedinTable42.Intermsofthemoreseriouspropertycrimes,whiletherewere3,178autotheftsin2015,therewerealso1,998breakandentersofaresidence,1,269breakandentersofabusiness,and511breakandenters‘other’.Combiningallthedifferenttypesofbreakandenters,theSurreyRCMPrecorded17.7breakandentersperday.Finally,therewerealsoasubstantialnumberofarsons(n=173)andalargenumberoftheftsover$5,000(n=167)in2015.

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Ineffect,excludingthemoreserioustypesofpropertycrime,approximatelythree-quarters(76.1percent)ofallpropertycrimewasofamoreminornatureinSurreyin2015.

TABLE42:PROPERTYCRIMEPROFILEFORSURREYIN2015

RawNumber(n=30,727) %ofTotal

TheftFromVehicle 7,224 23.5%OtherTheftUnder$5,000 4,663 15.2%MischieftoProperty 4,238 13.8%Frauds 3,698 12.1%AutoTheft 3,178 10.4%Shoplifting 2,618 8.5%Break&Enter–Residence 1,998 6.5%Break&Enter–Business 1,269 4.1%BikeTheft 576 1.9%Break&Enter–Other 511 1.7%PossessionofStolenProperty 327 1.1%Arson 173 0.6%OtherTheftOver$5,000 167 0.5%

GiventhelargepopulationofSurreyandthehighvolumeofpropertycrime,itwasnotunexpectedthatpropertycrimewouldbefoundthroughoutthecity.However,asdemonstratedinFigure23,thehighestconcentrationsofpropertycrimewerefoundinthreegeneralareas;twooftheseareaswerealongKingGeorgeHighwayinthewesternpartofthecity,andonehotspotwasfoundattheintersectionof104Avenueand152Street.Asexpected,thelatterhotspotwasfocusedaroundGuildfordTownCentre,whichisalargeshoppingcomplexspanningseveralcityblocksonbothsidesof152Street.ThehotspottowardsthenorthernendofKingGeorgeHighway,anditssurroundingareaofahighconcentrationofpropertycrimeisanothermulti-blockshopping,commercial,andrecreationalpartofthecityinWhalley.InadditiontoCentralCityMall,thisareaalsocontainsSurreyCentralTrainStation,SurreyLibraries,SurreyCityHall,andbordersHollandPark.Thereisalsoanoutdoorshoppingareawithseveralbigboxstores.ThethirdareawithahighconcentrationofpropertycrimewasalsoalongKingGeorgeHighwaybetween76Avenueand72Avenue.ThisareaischaracterizedbyanumberofoutdoorshoppingmallsonbothsidesofKingGeorgeHighway.

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FIGURE23:PROPERTYCRIMEHOTSPOTSINSURREYIN2015

Surreywasthetrueprototypicallowermainlandmunicipalitywithregardtostructuralexplanationsofpropertycrime.Whatwemightrefertoasthe“bigfour”factors,namelymedianhouseholdincome,theproportionofrenters,theproportionofunmarriedindividuals,andresidentialmobility,wereallinevidenceinSurrey(seeTable43).Infact,Surreypropertycrimehotspotsfeaturedsignificantlylowerincomelevelsandhigherlevelsofrenters,unmarriedindividuals,andresidentialmobility.Invirtuallyallotherrespects,Surreyareaswereindistinguishablefromeachother.Noneofthedifferencesinimmigration,Aboriginalpopulation,unemploymentrate,labourforceparticipation,levelofeducation,andhousingconditionbetweenhotspotsandnon-hotspotsinSurreyexceededthreepercentagepoints.Evenpopulationdensitywasnearlyidenticalinpropertycrimehotspotscomparedtothenon-hotspotareasofthecity.

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TABLE43:COMPARISONOFPROPERTYCRIMEHOTSPOTSANDNON-HOTSPOTS–SURREY

Hotspots Non-Hotspots tvaluePopulationDensity 3,798 3,838 -0.05PopulationChange2006-2011(%) 24.2% 18.3% 0.32YoungMales-Aged15-24(%) 6.1% 7.2% -2.03**Unmarried(%) 51.8% 38.8% 6.14**Mobility-Last5Years(%) 56.8% 41.1% 3.62**Immigration(%) 42.1% 39.6% 0.55AboriginalPopulation(%) 2.8% 1.9% 0.77MedianHouseholdIncome($) $44,132 $75,368 -9.49**UnemploymentRate 7.4 7.0 0.23LabourForceParticipation(%) 63.3% 65.2% -0.71LessThanHighSchoolEducation(%) 12.7% 12.1% 0.20Renters(%) 41.4% 24.7% 2.72**HousingCondition-MajorRepairs(%) 3.4% 2.1% 0.88*p<.10;**p<.05

WHITEROCK

In2015,WhiteRockhad988propertycrimesorjust2.7propertycrimesperday(seeTable45).Byvolume,WhiteRockranked18thoutofthe21jurisdictionsconsideredinthisreport.Evenwithalownumberofpropertycrimes,themostcommontypeofpropertycrimewastheftfromvehicle(25.5percent).Unliketheotherjurisdictionsexaminedinthisreport,thesecondmostcommonpropertycrimeoffenceinWhiteRockwasfraud(24.5percent).Itispossiblethatthehigherconcentrationofelderlypeople,aswillbediscussedbelow,andthelargenumberoftouriststhatvisitthisareaexplain,inpart,thefindingthatfraudwasthesecondmostcommonpropertycrimeinWhiteRockin2015.Intermsoftheothercommonpropertycrimetypes,mischieftoproperty(15.7percent),othertheftunder$5000(9.1percent),andautotheft(6.4percent)roundedoutthetopfive.Intermsofthemoreseriouspropertycrimes,whiletherewere63autotheftsin2015,therewerealso57breakandentersofaresidence,54breakandentersofabusiness,and12breakandenters‘other’.Combiningallthedifferenttypesofbreakandenters,theRCMPrecordedapproximatelyonebreakandentereverythreedays.Finally,therewerethreearsonsandthreeothertheftsover$5,000in2015.Ineffect,excludingthemoreserioustypesofpropertycrime,approximatelyfour-fifths(80.4percent)ofallpropertycrimewasofamoreminornatureinWhiteRockin2015.

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TABLE45:PROPERTYCRIMEPROFILEFORWHITEROCKIN2015

RawNumber(n=988) %ofTotal

TheftFromVehicle 251 25.5%Frauds 241 24.5%MischieftoProperty 154 15.7%OtherTheftUnder$5,000 90 9.1%AutoTheft 63 6.4%Break&Enter–Residence 57 5.8%Break&Enter–Business 54 5.5%BikeTheft 30 3.0%Shoplifting 16 1.6%Break&Enter–Other 12 1.2%PossessionofStolenProperty 10 1.0%Arson 3 0.3%OtherTheftOver$5,000 3 0.3%

Althoughtherewasarelativelylownumberofpropertycrimescomparedtosomeoftheotherjurisdictions,propertycrimewasdistributedthroughoutWhiteRock.Nonetheless,therewasonesubstantialhotspotthatwassurroundedbyalargehighdensityarea(seeFigure24).ThehotspotwasalongJohnstonRoadfromNorthBluffRoadtoRoperAvenue.WhiletherearesomecondominiumsalongJohnstonRoad,predominately,thisisashoppingareawithamixofsmallstores,restaurants,andcafes,inadditiontosomelargeroutsidemalls.

FIGURE24:PROPERTYCRIMEHOTSPOTSINWHITEROCKIN2015

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TheresultsfromtheanalysisofWhiteRockillustratedmuchthesamepatternasseenacrossothermunicipalitiesinthisstudy.Onceagain,lowermedianhouseholdincomewasthesinglebiggestfactorindistinguishingthepropertycrimehotspotfromnon-hotspotsinWhiteRock(seeTable46).TheWhiteRockhotspotwasalsomoredenselypopulated,containedmoreunmarriedindividuals,andhadlowerlabourforceparticipation.Therewasalsoastatisticallysignificantrelationshipdemonstratedbyimmigration,whichwasconsiderablyhigherinthehotspotanditssurroundinghighvolumeareacomparedtotherestofthecity.

TABLE46:COMPARISONOFPROPERTYCRIMEHOTSPOTSANDNON-HOTSPOTS–WHITEROCK

Hotspots Non-Hotspots tvaluePopulationDensity 8,230 3,617 4.86**PopulationChange2006-2011(%) 8.6% 1.1% 1.59YoungMales-Aged15-24(%) 2.7% 4.8% -3.45**Unmarried(%) 56.8% 43.2% 5.23**Mobility-Last5Years(%) 46.7% 44.1% 0.55Immigration(%) 31.4% 20.8% 3.87**AboriginalPopulation(%) 1.3% 1.3% -0.02MedianHouseholdIncome($) $43,941 $73,947 -5.38**UnemploymentRate 4.5 4.2 0.14LabourForceParticipation(%) 51.5% 65.1% -3.84**LessThanHighSchoolEducation(%) 2.3% 2.4% -0.04Renters(%) 35.1% 30.6% 0.83HousingCondition-MajorRepairs(%) 2.9% 4.3% -0.53*p<.10;**p<.05

THECITYOFVANCOUVER

Givenitssizeandpopulation,asexpected,Vancouverhadthehighestvolumeofpropertycrimecomparedtotheotherjurisdictionsanalysedinthisreport.In2015,Vancouverhad37,581propertycrimesorapproximately103propertycrimesperday.Whilethemostcommontypesofpropertycrimeweretheftfromvehicle(27.3percent)andothertheftunder$5000(15.3percent),unlikealloftheotherjurisdictions,thethirdmostcommonpropertycrimeinVancouverwasshoplifting(11.3percent).Thiswasfollowedbymischieftoproperty(10.5percent),and,again,uniqueforalargecitylikeVancouver,biketheft(8.1percent).Giventhis,onaverage,inatypicalday,theVancouverPoliceDepartmentrecorded28.1theftsfromvehicles,15.8othertheftunder$5,000,11.7shopliftingoffences,and3.8autothefts,inadditiontoalltheotheroffencetypespresentedinTable47.Intermsofthemoreseriouspropertycrimes,whiletherewere1,386autotheftsin2015,therewereevenmorebreakandentersofabusiness(n=2,459)andbreakandentersofaresidence(n=2,347),whiletherewereanadditional740breakandenters‘other’.Combiningallthedifferenttypesofbreakandenters,theVancouverPoliceDepartmentrecorded15.2breakandentersperday.Finally,therewerealsoasubstantialnumberofarsons(n=187)andothertheftsover$5,000(n=180)in2015.Still,evenwiththislargenumberofseriouspropertycrimes,approximatelyfour-fifths(80.5percent)ofallpropertycrimewasofamoreminornatureinVancouverin2015.

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TABLE47:PROPERTYCRIMEPROFILEFORVANCOUVERIN2015

RawNumber(n=37,581) %ofTotal

TheftFromVehicle 10,261 27.3%OtherTheftUnder$5,000 5,755 15.3%Shoplifting 4,258 11.3%MischieftoProperty 3,940 10.5%BikeTheft 3,056 8.1%Frauds 2,624 7.0%Break&Enter–Business 2,459 6.5%Break&Enter–Residence 2,347 6.2%AutoTheft 1,386 3.7%Break&Enter–Other 740 2.0%PossessionofStolenProperty 375 1.0%Arson 187 0.5%OtherTheftOver$5,000 180 0.5%

GiventhelargepopulationofVancouverandthehighvolumeofpropertycrime,itwasnotunexpectedthatpropertycrimewouldbefounddistributedthroughoutthecity.12However,asdemonstratedinFigure25,thehighestconcentrationsofpropertycrimecoveredalargeamountofterritoryfromBurrardStreettoColumbiaStreetandbetweenNelsonStreettoWaterStreet.ThisareaincludesGastownandthedowntowncoreofVancouver.

12DuetothehighdensityofpropertycrimeinandaroundtheDowntownEastsideinVancouver,thedensitymapsuggeststhattherewerelargeportionsofVancouverwithlowlevelsofpropertycrime.Whilethisisaccurate,thenatureofthedensitymapcangivethefalseimpressionthattherewasvirtuallynopropertycrimeinmanypartsofthecity.Conversely,itisimportanttonotethatpropertycrimewasfoundthroughouttheentireCityofVancouver.

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FIGURE25:PROPERTYCRIMEHOTSPOTSINVANCOUVERIN2015

Inmostrespects,asexpected,theCityVancouvercloselymirroredSurreywithregardstoastructuralaccountingofpropertycrime.LikeSurrey,propertycrimehotspotandnon-hotspotareasinVancouverweredifferentiatedbythe“bigfour”factors;medianhouseholdincome,theproportionofrenters,theproportionofunmarriedindividuals,andresidentialmobility(seeTable48).Asusual,thelargehotspotinVancouverwascharacterizedbycomparativelylessincome,morerenters,moreunmarriedindividuals,andmoreresidentialmobility.Itisalsoworthnotingthat,unlikeSurrey,theVancouverhotspotanditssurroundinghighvolumepropertycrimeareawasmuchmoredenselypopulatedcomparedtotherestofthecity.AlsoincontrasttoSurrey,immigrationvariedsignificantlybetweenthehotspotandtheotherpartsofthecity.Morespecifically,inVancouver,thehotspotareahadproportionatelyfewerimmigrantscomparedtothenon-hotspotareas.

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TABLE48:COMPARISONOFPROPERTYCRIMEHOTSPOTSANDNON-HOTSPOTS–VANCOUVER

Hotspots Non-Hotspots tvaluePopulationDensity 18,264 9,290 4.75**PopulationChange2006-2011(%) 13.4% 2.4 0.97YoungMales-Aged15-24(%) 6.0% 6.2 -0.27Unmarried(%) 64.9% 49.0 7.38**Mobility-Last5Years(%) 68.3% 43.9 7.07**Immigration(%) 32.6% 44.0 -3.57**AboriginalPopulation(%) 1.9% 1.4 0.66MedianHouseholdIncome($) $44,772 $65,533 -3.34**UnemploymentRate 8.3 6.0 0.76LabourForceParticipation(%) 68.2% 66.6% 0.41LessThanHighSchoolEducation(%) 4.6% 7.6% -1.54Renters(%) 68.8% 44.9% 6.48**HousingCondition-MajorRepairs(%) 4.8% 6.1% -0.71*p<.10;**p<.05

WESTVANCOUVER

In2015,WestVancouverhad1,404propertycrimesorapproximately3.8propertycrimesperday(seeTable49).Injustconsideringtherawnumberofpropertyoffences,WestVancouverranked15thoutofthe21jurisdictionsconsideredinthisreport.Unlikeanyoftheotherjurisdictions,themostcommonpropertycrimeinWestVancouverwasshoplifting(22.4percent)followedcloselybytheftfromvehicle(21.9percent).Thenextthreemostcommonpropertycrimesweremischieftoproperty(13.6percent),fraud(10.8percent),andothertheftunder$5000(10.8percent).Intermsofthemoreseriouspropertycrimes,in2015,therewereonly27autothefts,74breakandentersofaresidence,38breakandentersofabusiness,and62breakandenters‘other’.Combiningallthedifferenttypesofbreakandenters,theWestVancouverPoliceDepartmentrecordedonebreakandenterapproximatelyeverytwodays.Finally,therewereveryfewarsons(n=6)andasmallnumberoftheftsover$5,000(n=14)in2015.Ineffect,excludingthemoreserioustypesofpropertycrime,morethanfour-fifths(84.2percent)ofallpropertycrimewasofamoreminornatureinWestVancouverin2015.

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TABLE49:PROPERTYCRIMEPROFILEFORWESTVANCOVUERIN2015

RawNumber(n=1,404) %ofTotal

Shoplifting 314 22.4%TheftFromVehicle 307 21.9%MischieftoProperty 190 13.6%Frauds 151 10.8%OtherTheftUnder$5,000 152 10.8%Break&Enter–Residence 74 5.3%Break&Enter–Other 62 4.4%BikeTheft 48 3.4%Break&Enter–Business 38 2.7%AutoTheft 27 1.9%PossessionofStolenProperty 18 1.3%OtherTheftOver$5,000 14 1.0%Arson 6 0.4%

AsdemonstratedinFigure26,in2015,WestVancouver’spropertycrimewasconcentratedalongthesouthernpartofthecity,alongthecoastoftheBurrardInlet.Therewasonehotspotfor2015anditwasalongMarineDrivefromTaylorWaytoPoundRoadinthesouth-easternpartofthecity.Asexpected,thisisthemainshoppingareainWestVancouvercharacterizedbyalargeoutsideshoppingmallonthenorthsideofMarineDriveandtheParkRoyalShoppingCentreandseveralbigboxstoresonthesouthsideoftheroad.

FIGURE26:PROPERTYCRIMEHOTSPOTSINWESTVANCOUVERIN2015

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LikePittMeadowsandWhistler,noneofthestructuralvariablesreachedtherequiredleveltobeconsideredstatisticallysignificanceinWestVancouver(seeTable50).Still,manyoftherelationshipswereintheanticipateddirection,buttheeffectswerenotlargeenoughtodistinguishtheonemainhotspotinWestVancouverfromtherestofthecity.Forexample,thehotspotinWestVancouvercontainedagreaterproportionofunmarriedpersonsandrenters,hadhigherlevelsofresidentialmobility,lowermedianhouseholdincomelevels,andreducedparticipationinthelabourforce.However,thedifferencesbetweenthehotspotandthenon-hotspotareasonthesefactorswasquitesmall,andnotstatisticallysignificant.

TABLE50:COMPARISONOFPROPERTYCRIMEHOTSPOTSANDNON-HOTSPOTS–WESTVANCOUVER

Hotspots Non-Hotspots tvaluePopulationDensity 2,071 2,434 -0.20PopulationChange2006-2011(%) -1.0% 0.7% -0.11YoungMales-Aged15-24(%) 5.1% 7.0% -0.83Unmarried(%) 43.1% 38.9% 0.64Mobility-Last5Years(%) 33.9% 36.2% -0.25Immigration(%) 41.4% 39.6% 0.18AboriginalPopulation(%) 0.0% 0.4% -0.29MedianHouseholdIncome($) $70,936 $103,875 -1.12UnemploymentRate 9.0 4.7 0.97LabourForceParticipation(%) 47.5% 54.4% -0.79LessThanHighSchoolEducation(%) 0.0% 0.1% -0.27Renters(%) 25.5% 14.3% 0.73HousingCondition-MajorRepairs(%) 1.5% 3.6% -0.49*p<.10;**p<.05

SUMMARYOFVARIABLEEFFECTS

Althoughtheprecedinganalysesfocusedonthemunicipalities,Table51indicatesthatthereweresomeimportantfindingswhentheresultsofalloftheseanalysesarepooledtogether.Asmentionedpreviously,therewerefourvariablesthatconsistentlydemonstratedsignificantpredictiveeffects;medianhouseholdincome,theproportionofrenters,theproportionofunmarriedindividuals,andresidentialmobility.Thepercentageofrenterswasasignificantpredictorofcrimeacrossslightlymorethantwo-thirds(68percent)ofallmunicipalities,whileresidentialmobilityandtheproportionofunmarriedpersonswaspresentinoverthree-quarters(76percent)ofthecities.Medianhouseholdincomewassubstantiallyrelatedtopropertycrimehotspotsin18ofthe21municipalities(86percent).Ifthethreemunicipalitiesthatdidnotshowanysignificanteffectsareexcluded,medianhouseholdincomewasasignificantfactorineveryanalysis.

Attheotherendofthespectrum,somevariableswererarelysignificantindifferentiatingpropertycrimehotspotsfromnon-hotspotsinacity.ParticularlynoticeableinthisregardweretheproportionofAboriginalpeople,theunemploymentrate,andpopulationchange.Variableswithmoresporadiceffectsincludedlabourforceparticipation,theproportionofresidentswithlessthanahighschooleducation,recentimmigration,andpoorhousingcondition.

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TABLE51:SUMMARYOFSIGNIFICANTTVALUESACROSSMUNICIPALITIES

Abbotsford

Burnaby

Chilliwack

Coquitlam

Delta

Hope

Langley

MapleRidge

Mission

New

Westminster

NorthVancouver

PittMeadow

s

PortCoquitlam

PortMoody

Richmond

Squam

ish

Surrey

Vancouver

WestVancouver

Whistler

WhiteRock

PopulationDensity

* ** * *

** ** ** * ** *

** **

PopulationChange

*

*

YoungMales ** ** ** ** ** ** ** ** ** ** **

Unmarried ** ** ** ** ** * ** ** ** ** ** ** ** ** ** **

Mobility ** ** ** ** ** ** ** ** * ** ** ** ** ** ** **

Immigration ** * ** ** ** ** ** **

AboriginalPopulation

** *

MedianHouseholdIncome

** ** ** ** ** * ** ** ** ** **

** ** ** ** ** **

**

UnemploymentRate

* **

LabourForceParticipation

** * ** ** ** *

** **

<HighSchoolEducation

** * ** ** *

* *

Renters * ** ** ** * ** ** ** ** ** ** ** ** **

HousingCondition

** * *

** * ** **

*p<.10;**p<.05

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RecommendationsBasedonthenature,quantity,andlocationsofpropertycrimethroughouttheLowerMainlandDistrict,thereareanumberofrecommendationsforthepolicetoaddresstherecentincreasesinpropertycrimerates.

1.FOCUSONINFORMATIONANDINTELLIGENCE-LEDSTRATEGIESTOCOMBATPROPERTYCRIME

Tobeanintelligence-ledorganization,policingagenciesmustcollect,analyze,anddisseminatevastamountsofinformationtomakedecisionsaboutthebestprograms,strategies,andprojectstoreducepropertycrime.Inordertodothiswell,crimeanalystsshouldhaveagoodworkingrelationshipwithbothgeneraldutymembersandtheinvestigativeservicesdivisionsinanypolicingagency.Ideally,crimeanalystsshouldbeassignedtodifferentsections,bothgeneraldutyandpropertycrimeunits,asthiscanhelpimprovetheamountofworkableintelligencebeingproducedbyanalyststhatissharedwiththoseunits.Italsoservestoimprovetheworkingrelationshipsbetweenthesectionsandtheanalysts,asanalystsdevelopabetterunderstandingofeachunit’sneedsandpriorities,whileofficersinthoseunitscanlearnaboutwhatanalystscanproduce,andwhattypeofintelligenceisneededbytheanalyststoproducequalityproducts.

Itisnotenoughtosimplyhireanalysts;policingagenciesmustcreateacultureofusingdataandanalysistoinformprojectsandstrategies.Theremustbeacommitmentfromthepoliceagencytoensurethatallanalystsreceivethenecessarytraining,and,asthisfieldisconstantlyevolving,consistentaccesstorefreshercoursesortraininginnewtechniquesandnewsoftwaresolutions.Intermsoftheproductsproducedbyanalysts,itisnecessarythattheproductstheyprovidearetimely,relevant,andspecifictotheproblemsfacedbythepolicingagency.

Withthehelpofcrimeanalysts,policingagenciescanremainfocusedonspecificcrimeproblems,prolificandpriorityoffenders,andprolificcrimelocations.Thismightincludeincreasingvehicle,bike,andfootpatrolsinareasathighpropertycrimevolumetimes,increasingthenumberofvolunteersatstrategicallyselectedtimesandlocationstodeterpotentialoffenders,increasingthecommunicationbetweenthepoliceandthecommunityinandaroundpropertycrimehotspotsaboutthenatureofpropertycrime,policeinitiativestoreduceandpreventpropertycrime,thethingsthatresidentsorbusinessownerscandotoreduceandpreventpropertycrime,andenhancingmeaningfulpartnershipsbetweenthepoliceandbusinessesandresidents.

2.ARENEWEDFOCUSONPROLIFICOFFENDERS,LOCATIONS,ANDPROBLEMS

Researchhasshownthatalargeproportionofpropertycrimeisgenerallycommittedbyarelativelysmallnumberofindividuals,oftenreferredtoasprolificorpriorityoffenders(Cohen,Plecas,McCormick,&Peters,2014).Duetothis,itiscriticalforpolicingorganizationstoidentifyandfocusonprolificandpriorityoffenders,aswellashotspotpropertycrimelocations,andspecificsocialissueswithinthecommunitythatcontributetopropertycrimerates.Specifically,inregardstopropertycrime,issuessuchastheftfromandtheftofvehicles,shoplifting,mischiefto

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property,andothertheftunder$5,000areallcommonproblemsinthecitiesthatcomprisetheLowerMainlandDistrict.ItisvitalfortheRCMPandpolicedepartmentstofocusonthoseprolificoffendersknowntocommitthesetypesofcrimes,andcontinuallyconcentrateontheareasknowntobehotspotsforpropertycrime.Asmentionedabove,regularandconsistentanalysisofalocationorcrimetypecanbeusedtodirectthefocusofpoliceofficersinanefficientandeffectivewaytoreduceandpreventpropertycrime.

Oneofthegreatestchallengesforpoliceismanagingandbeingproactivewiththeirprolificandchronicoffenders,locations,andproblems.Policeagencieshaveacknowledgedtheneedtofocusonthishighlyactivegroupofoffenders,addressthelocationsthatareaconsistentdrainonpoliceresources,andsolvethemainsocialproblemsthatcontributetopropertycrimeinthecommunity.Thestrategiesforfocusingontheseoffenderscanvary,buttypically,policingagenciestendtoutilizeoneormoreunits,suchasGeneralDuty,ProlificOffenderUnits,YouthUnitorCrimeReductionUnits,totargetthesepersons,locations,andproblems.Muchliketheissueofproactivepolicing,whichwillbediscussedbelow,theresponsetoprolificandpriorityoffenders,locations,andproblemsbythepolicerequiresthecommitmentofeveryoneintheagency.Addressingprolificpropertyoffendersandlocationscannotbethemandateofasinglespecializedunit,but,again,mustbeseenasacorepolicingfunctionthatinvolvesthesharingofinformationandresourcesacrossthedetachmentordepartment.

Itcannotbeoverstatedhowimportantitis,foroverallpublicsafety,aswellaspropertycrimeingeneral,tobeeffectiveagainstprolificandpriorityoffenders,aswellaschronicpropertycrimelocations,andthesocialproblemsthatcontributetopropertycrimerates.Asstatedabove,strategiesfordealingwithprolificoffenders,locations,andproblemsmustbedrivenbyintelligenceandinformation-led,collectedbyofficersandthecommunity,andprocessedbycrimeanalystsintomeaningfulandstrategicstrategiesandprograms.

3.ACONTINUEDCOMMITMENTTOCRIMEPREVENTIONTHROUGHENVIRONMENTALDESIGN(CPTED)

CrimePreventionthroughEnvironmentalDesign(CPTED)isastrategyoftenlinkedtoroutineactivitytheoriesofcrime,andisasituationalcrimepreventionmethoddesignedtoreduceandpreventawiderangeofoffences,includingpropertycrime.Asdiscussedabove,routineactivitytheorysuggeststhatcrimeoccurswhenamotivatedoffender,asuitabletarget,andalackofacapableguardianmeetintimeandspace.MakingchangestothephysicalenvironmentoraparticularlocationinanattempttomakeitlesssuitableormoredifficultforanoffendertocommitacrimeisthegoalofCPTED.Forexample,ifabusinesshasbeenatargetofmultiplebreak-ins,theownermightconsiderinstallinganalarmsystem,installingbarsonthewindows,ensuringthebusinessisvisiblefromthestreet,orincreasingthelightinginsideandoutsidethebusinessinanattempttopreventbeingatargetofcrime.OtherCPTEDexamplesmightincludelandscapingtoimprovevisibilityandthesafetyofpeoplewalkinginthearea,hiringprivatesecurityguardstosupervisealocation,orplacinglightstoilluminatedarkareaswhereacriminalmighthideorbeingabletoengageinanoffence.Ideally,thesetypesofsolutionswouldfitthecrimeproblemsinthatspecificarea,andshouldbedonewiththeguidanceofaCPTEDprofessional.

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4.BUILDMEANINGFULRELATIONSHIPSWITHCOMMUNITYSTAKEHOLDERS

Manypropertycrimereductionstrategiesrelyontheestablishmentandmaintenanceofeffectivepartnershipsbetweenpoliceandcommunitystakeholders(Cohen,Plecas,McCormick,&Peters,2014).Policecannotworkinisolationwhenattemptingtosolvecrimeissueswithinacommunity,particularlywithaproblemsuchaspropertycrime,whichisoftenlinkedtosocialproblemslikeaddiction,homelessness,andpoverty.Instead,thepoliceneedtobuildrelationshipswithagenciesthataredesignedtobemoreeffectiveandefficientatdealingwiththosetypesoflargescalesocialproblems.Establishingthesetypesofcollaborativerelationshipswithotheragenciesinthecommunityreflectsthatcrimeisnotsimplyapolicingissue,buttheresponsibilityoftheentirecommunity,andaproblemthatcannotbesolvedbythepolicealone.

Therearenumerousexamplesofagenciesthathavebeenabletoassistthepoliceinreducingorpreventingpropertycrime,suchashomelessshelters,addictiontreatmentfacilities,healthcareagencies,privatesecurityagencies,andschools.Therearealsoseveralexamplesofcommunityprogramsthatcouldbeusedinanattempttodrivedownpropertycrimeinalocationidentifiedasahotspot,suchascrimefreemulti-housing,orblockwatchorneighbourhoodwatchprograms.Thesetypesofprogramstendtoworkbestwhendonewiththeassistanceandguidanceofthepolice.Assuch,inadditiontopoliceagencieshavingthenecessaryresourcestoeffectivelyaddresstheissuesthatcontributetopropertycrime,establishingandmaintainingmeaningfulpartnershipswiththosecriminaljustice,non-governmental,andcommunityagenciesthatareinabetterpositiontoaddresstheunderlyingissuesthatcontributetopropertycrimeinacommunitywouldcontributetoanoverallreductioninpropertycrime.Giventhis,itisrecommendedthatthepolicecontinuetodevelopandexpandpartnershipswiththoseagencies,groups,andstakeholderstocombatpropertycrime.

Boththestyleandsubstanceofcommunityoutreachonthepartofthepolicemustbetailoredtospecificneighborhoods.Themake-upandnatureofpropertycrimehotspotsinacityvariessubstantiallyfromotherareasofthesamecity.Theseareasaremuchmorelikelytofeatureresidentswhoarepoor,transient,andunattached.Thesecharacteristicsposespecialchallengesforbuildingcommunity-policerelations.

5.EMPHASIZEPROACTIVEPOLICINGSTRATEGIES

Inordertoavoidthemorecommonoccurrencethatmuchoftheproactivepolicingthatiscurrentlybeingundertakenbythepoliceisnotintelligenceorinformation-led,andthatitoccursinveryshortsegmentswhengeneralmembershavetimebetweenrespondingtocallsforservice,policeagenciesshouldconsiderthemeritsofdedicated,consistentproactivepolicingapproaches.Forexample,thedetachmentorpolicedepartmentshouldconsiderassigninganumberofmembersorofficersandvehicles,determinedbythesizeofthepoliceforceandthepropertycrimeratesinthecommunity,todedicatedproactivepatrol.Theseofficersormemberswouldbedirectedbythedetachment’scrimeandintelligenceanalyststopatrolspecificareasandwalkthroughcertainlocations,suchasashoppingmall,atspecifictimesdeterminedbytheanalyststobemosteffectiveatdeterringpropertycrime,creatingavisiblepresenceinthecommunity,andengaginginanumberofproactivepolicingstrategiesasrequiredbycrimetrenddataorcommunityneeds.This

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wouldnotreplaceallmembersengaginginproactivepatrollingwhennotrespondingtocallsforservice,butwouldensurethatissuesorproblemlocationsthatwouldbenefitfromproactivepatrollingreceivethenecessaryattention.

Asecondapproach,whichwouldavoidcreatingaspecial‘proactivepatrolling’unitwithinGeneralDuty,wouldinvolvesettingasideaspecificamountoftime,forexample30%ofshifttime,ineachgeneraldutymember’sorofficer’sshiftdedicatedexclusivelytoproactivepatrolling.Whilethismightbemoredifficulttoscheduleasgeneraldutymembersorofficersmightbeatacallforservicewhentheirproactivepatrollingtimeissettobegin,ortheremaybethosewhoareuninterestedornotverygoodatproactivepatrolling,thebenefitofthisapproachisthatitspreadstheresponsibilityforproactivepatrollingacrossallgeneraldutymembersorofficersandreinforcesthemessagethatthisisacorepolicingfunction.

Thethirdapproachmightbetoassignoneshiftfromeachgeneraldutymember’sorofficer’stypically4-on-4-offshiftingscheduletoproactivepolicing,duringwhichthememberorofficerwouldspendthatentireshiftengagedintargetedproactivepolicing.Thebenefitofthisapproachisthatitavoidsaspecializedunitandavoidsthechallengeoffindingsometimeineachshifttoengageprimarilyinproactivepolicingstrategies.Theshortcomingsofthisapproacharethatitwillincludetimesduringashiftwherethereisnotaneedforproactivepolicingforpropertycrimeandwillincludemembersorofficerswhoareeitheruninterestedornotverygoodatproactivepolicing.Regardlessofthemethodselected,supervisorsshouldanalyzethedrivingpatternsofgeneraldutymembersorofficerstoensurethattheyareintherightlocationsattherighttimesofthedayornight,andfortherightamountoftime,toeffectivelyandefficientlycontributetoproactivepolicingtoreduceandpreventpropertycrime.Itshouldalsobenotedthatallgeneraldutyproactivepolicinginitiativesshouldbetiedintotheeffortsofothersectionsandunitsthatalsoengageinroutineproactivepolicingtobetterintegratethework,intelligence,andinformationcollected,buttoalsorecognizethatproactivepolicingisnotthesoleresponsibilityofsome,butacorepolicingfunctionacrosstheentiredetachmentordepartment.Whilenotasubstitute,thepoliceagencyshouldalsoconsiderincludingtheirAuxiliaryorvolunteermembersinthisstrategy.Forexample,thesepeoplecoulddrivearoundtoincreasepolicevisibilityinhotspotlocationsatstrategictimestoreduceandpreventpropertycrime,aswellasprovidemoreopportunitiesforthepolicetopositivelyengagewiththepublic.

6.INCLUDETRAFFICSERVICESINPROPERTYCRIMEPREVENTION

Ashighlightedbytheotherrecommendationsmadeinthisreport,itisbecomingincreasinglynecessaryforthepolice,includingtrafficservices,tobecomemoreproactive,tofocusonpriorityandprolificoffenders,toestablishandmaintainmeaningfulpartnershipswithotherstakeholders,andtobecomemuchmoreinformation-ledandevidence-based.Giventhis,DataDrivenApproachestoCrimeandTrafficSafety(DDACTS)isanoperationalmodelthatcombinestheanalysisofcrimeandtrafficdatatoinformeffectiveandefficientmethodsfordeployinglawenforcementandotherresourcestospecificlocationstotargetcertaindrivingbehaviours,aswellascriminalbehaviorsandoffenders,includingpropertycrime.DDACTSisbasedonbeinginformationandintelligenceled,isproactiveandpreventative,andisproblem-oriented.Atitscore,DDACTSinvolve

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determiningwhenandwherearethehighdensitiesforbothtrafficsafetyissuesandcrime,andputtingtrafficenforcementinthatlocationtoreduceorpreventthesebehaviours.

Theapproachissuccessfulbecause,asdemonstratedthroughoutthisreport,propertycrimeisnotevenlydistributedthroughoutajurisdiction,butisclusteredinspecificlocations.Thisisalsotrueoftrafficsafetyissues.TheevidencethatsupportstheunderlyingtheoreticalframeworkforDDACTSisthatcrimeandcrashesoftenoccurincloseproximitytoeachother,crimesofteninvolvestheuseofamotorvehicle,andoffendersfrequentlyuseavehicletotraveltoandfromthesceneofacrime.Moreover,trafficstopsareanextremelyvaluablelawenforcementtoolbecause,inadditiontocollectingvehicleinformationandenforcingtrafficviolations,vehiclestopscanyieldimportantintelligenceandcanuncovercrimesandcriminalassociations.Whenimplementedwell,DDACTScanreducecrimeandincreasepublicsafety,increasepublicinvolvementinreducingcrime,increasetheintegrationofstakeholders,improvepublicawarenessandbehaviour,andefficientlydeploylimitedpoliceresources.

7.INCREASINGTHEPUBLIC’SAWARENESSABOUTPROPERTYCRIME

Obviously,oneeffectivemethodofreducingtheftfromvehicles,othertheftunder$5,000,andmischieftopropertyoffencesistodecreasetheopportunitytocommitcrimeinthefirstplace.Publicawarenessaroundtheftfromvehicles,warningownersnottoleaveanythingofvalueintheirvehicle,andkeepingtheglovecompartmentorothercompartmentsinthecaremptyandopenareeffectivetacticstoreducethistypeofoffence.Similarly,improvedsecurityincommercialareas,suchasCCTVorsecuritypatrolsinparkinglots,increasedlightingduringtheevenings,andbettervisibilityfromthestreethavealsodemonstratedanabilitytoreducetheopportunityforanoffendertobreakintoavehicle,engageinmischieforvandalismlateatnight,orattemptabreakorenteroratheftofvehicle,particularlyinandaroundacommercialproperty.

Britton,Kershaw,Osborne,andSmith(2012)pointedoutthatstrategiesaimedatreducingrepeatvictimizationhavebeenveryeffectiveintheUnitedKingdom.Thesestrategieshavefocusedonpoliceorotherlawenforcementagenciesmeetingwithvictimsofpropertycrimetoshowthemhowtoreducepotentialopportunitiesforpropertycrimeoffendersaroundtheirhomeorbusiness.ThesetechniqueshavereducedthenumberofrepeatpropertycrimevictimsintheUnitedKingdom,andcouldbeapromisingareatofocusonintheLowerMainlandDistrict.Thiswouldprovidetheopportunityforapolicingagencytoshareinformationaboutcrimepreventionthroughenvironmentaldesigntoapropertyowner,whichhasbeenshowntobeeffectiveinreducingpotentialopportunitiesforoffenderstocommitcrime(Cozens&Love,2015).Additionally,thepolicecouldsharepropertycrimepreventionstrategiesforthehometotargethardenresidencesandbuildingagainstpropertycrime.

ConclusionBasedonananalysisofthedataintheLMDfrom2001to2014,itisclearthattherehasbeenasubstantialdropinthevolumeofpropertycrimeacrosstheLMDandineachofthe22municipalitiesthatmakeuptheLMD.However,itisalsotruethattherehasbeenanincreaseinthe

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propertycrimeratesinmanyoftheLMD’sjurisdictionsoverthepasttwotothreeyears.Still,evenwiththesemodestincreasesintherecentpast,theLMDasawholeandeachcitywithininhavemaintainedpropertycrimerateswellbelowtheirpeakyears.

Itisalsoimportanttokeepinmindthatthevastmajorityofpropertycrimein2015(78.5percent)wasmadeupofthelessseriousformsofpropertycrime.Withonlysomesmallvariationsbycity,themostcommonformsofpropertycrimeweretheftfromvehicles,othertheftunder$5,000,mischieftoproperty,andshoplifting.Giventhis,itwasnotunexpectedthat,forthemostpart,propertycrimehotspotsineachofthecitiestendedtofocusinandaroundthemaincommercialpartsofthecityandthelowerincomeresidentialzonesnearthem.Thisfindingwasfurthersupportedbytheanalysesofthesocio-economic,socio-demographic,andcompositionalfactorsineachcitythatdistinguishedthepropertycrimehotspotareasfromtherestofthecity.Here,therewerefourvariablesthatconsistentlydemonstratedsignificantpredictiveeffects.Theseweremedianhouseholdincome,theproportionofrenters,theproportionofunmarriedindividuals,andresidentialmobility.Attheotherendofthespectrum,somevariableswererarelysignificantindifferentiatingpropertycrimehotspotsfromnon-hotspotsinacity;namely,theproportionofAboriginalpeople,theunemploymentrate,andpopulationchange.

Inconclusion,thepropertycrimerateintheLMDhasbeenincreasinginthepastfewyears,butisalongwayofffromitspeakintheearly2000s.ThisreporthasdetailedthenatureandtypeofpropertycrimeexperiencedwithineachmunicipalityoftheLMD,thedistributionorspreadofpropertycrimewithineachcityoftheLMD,andprovidedsomeinsightintothesocial,demographic,economic,andcompositionfactorsthatdistinguishpropertycrimehotspotsfromnon-hotspotsineachcity.Thisreportalsoprovidedanumberofrecommendationsforpoliceagenciestoimprovetheirabilitytopreventandreducethevolumeofpropertycrimeintheirjurisdictions.ItisclearthatpoliceagenciesthroughouttheLMDareawareoftherecentupwardstrendinpropertycrimeinmanypartsoftheLMD,andthattheyareengaginginanumberoftraditionalandproactivestrategiestoaddressthisissue.Theinformationinthisreportshouldassistpoliceleadersinfurtherdevelopingspecificanti-propertycrimeresponsesbyhighlightingtheirparticularpropertycrimeprofile,theirpropertycrimehotspots,andthosespecificsocial,economic,demographic,andcompositionsfactorsthatcontributemosttopropertycrimeintheircities.

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