ability, temperament, and interests ... - personality project · part of the international...

TAI SAPA Measures TAI and niche selection Summary References

Ability, Temperament, and Interests:their joint predictive power for job choice

The International Society for the Study of IntelligenceAlbuquerque, New Mexico

William Revelle and David Condon

Northwestern UniversityEvanston, Illinois USA

Partially supported by a grant from the National Science Foundation:SMA-1419324

September 19, 2015http://personality-project.org/sapa.html

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http://personality-project.org/sapa.html


Outline

Temperament, Abilities, and Interests: considering appetites andaptitudes

Method: Synthetic Aperture Personality Assessment (SAPA)SAPA theoryDemographics

MeasuresInternational Cognitive Ability Resource: ICARTemperament and Interests

Temperament, Ability and Interests: Occupational ChoicePooled correlations 6= within group or between groupcorrelationsOccupational Choice as niche selection

Summary

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Personality, prediction, and life outcomes

1. Has long been known that to predict real world outcomes weneed more than just ability (Kelly & Fiske, 1950, 1951; Deary, 2008; Roberts, Kuncel,

Shiner, Caspi & Goldberg, 2007).

2. Jobs differ in their intellectual requirements (Gottfredson, 1997).

3. We would add that there are also temperamentalrequirements.

4. We will consider individual differences in Temperament,Ability, and Interests as they relate to niche selection inoccupational choice (Bouchard, 1997; Hayes, 1962; Johnson, 2010) .

3 / 27


Measuring individual differences

1. A basic problem in the study of individual differences is thatthere are so many different constructs that interest us. Theseinclude constructs from at least four broad domains

• Temperament• Ability• Interests• Character

2. Each domain has many constructs• Dimensions of Temperament 2-3-5-6-15?• Structure of Ability (g - gf , gc , V-P-R)?• Hierarchical structure of interests people-things, RIASEC• Range of possible measures of character

3. In addition, showing the utility of TAIC measures requirescriterion variables, and should include demographics.

4. Our solution: Use basic sampling theory as discussed by Lord(1955) sampling items as well as people.

4 / 27


SAPA theory

Subjects are expensive, so are items

1. In a survey such as MTURK, we need to pay by the personand by the item.

2. Why give each person the same items? Sample items, as wesample people.

3. Synthetically combine data across subjects and across items.This will imply a missing data structure which is

• Missing Completely At Random (MCAR), or even moredescriptive:

• Massively Missing Completely at Random (MMCAR)

4. This is the essence of Synthetic Aperture PersonalityAssessment (SAPA).

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SAPA theory

3 Methods of collecting 256 subject * items dataa) 8 x 32 complete

4621363452114345344364533121241421243623166421516154432261516513516613511551654636222244356233441114134336233221561215213561452225353121264561433433232246526411613351545664241146126412253535162463434215153624242541351343511611554654453123111162423325516334

b) 32 x 8 complete4632311425443314433154232631414541435614422361536242134435234443345141666341515444441342135143216636566312264546314661353264551466151251144114416244363633316236633254251153112661155546332453615224165463212356244146636366141445555223143644332146141633232365

c) 32 x 32 MCAR p=.25..3..2..6.....4.55.......44................4..6..45..3.4..6....16..3.......6.1.....6.2.......5.6....3522......5.3...3......5........3.2.2.......3..2......65..5......51....324.........23......5....552............25...54.5.......44.4.5....3..6...6........3......61.523.2....2...........3...5.............42.4..6.5......61.....3....3.6..1.4...1..5......5.1....54..........2.4.33..6......4.....52..6.....44.3...........2..44...1........1..42....5..1.....1..3.......2..3.521.......6..........3.142.........22......12..4...2..........3..162...4.....4..4..6..3.4...1....5.33.........5..........243..5....41......1....5..3..4...4.4..5..1.........4......4.......3..5.2.....64.4..4....1.1.2...6....4......55....2.......3..2..53.....2..2.3.3............1...2..43...3.13........5....2.........4..54...2.3..62....22.......332..1.....5......6.......5..3.4.....3....5.241..............63.1.......6...5..4..2...5..2.4..5..........52.4.....44...2.55.....2.....6.....6.....55.....5..........4....6341.4..2.........55......5.......45....3..32.

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SAPA theory

Synthetic Aperture Personality Assessment

1. Give each participant a random sample of pn items takenfrom a larger pool of n items.

2. Find covariances based upon “pairwise complete data”.3. Find scales based upon basic covariance algebra.

• Let the raw data be the matrix X with N observationsconverted to deviation scores.

• Then the item variance covariance matrix is C = XX ′N−1

• and scale scores, S are found by S = K ′X .• K is a keying matrix, with K ij = 1 if itemi is to be scored in

the positive direction for scale j, 0 if it is not to be scored, and-1 if it is to be scored in the negative direction.

• In this case, the covariance between scales, C s , is

C s = K ′X (K ′X )′N−1 = K ′XX ′KN−1 = K ′CK . (1)

4. That is, we can find the correlations/covariances betweenscales from the item covariances, not the raw items.

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Demographics

Our data

Time Frame Data collected at personality-project.org andsapa-project.org from August 18, 2010 toSeptember 10, 2015

Subjects N = 191,893 (71,438 males, 120,454 females)

Materials 947 items (696 temperament, 60 ability, 212interests, 39 demographic)

Scales used 15 Temperament, 4 Ability, 6 Interests

N in workforce N =74,708

Occupations 973 separate occupations, following a Paretodistribution with ≈ 80% represented by the top 20%of occupations

N ≥ 75 195 occupations for 55,902 participants

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personality-project.org

sapa-project.org


Demographics

Median Age is 22. 63% Female

Age by males and females

count

Age

Age by males and femalesAge

020

4060

80

10000 5000 0 5000 100009 / 27


Demographics

81,200 students, 74,708 in the labor force

Gender and Occupationcount

Gender and Occupation

40000

20000

0

20000

40000

Student not work seeking w. Homemkr Employed Retired10 / 27


Demographics

Of employed: 43% have ≥ a college education, 39% are in college

Gender and Educationcount

Gender and Education

20000

10000

0

10000

20000

< 12 High Sch in Coll < 16 BA/BS in Grad Grad/Pro11 / 27


abiliy:ICAR

The International Cognitive Ability Resource

1. An international collaboration to develop open sourcecognitive ability items.

2. ICAR:Ability::IPIP:Personality3. http://www.icar-project.com/

4. News letter at http://www.icar-project.com/ICAR_News_Issue_One.pdf

5. Key organizersGermany Phillip Doebler (Munster and Ulm) and Heinz

Holling (Munster)U.K. Luning Sun and John Rust (Cambridge)

U.S.A William Revelle and David Condon(Northwestern)

6. Everyone is welcome to join7. Supported by Open Research Area (ORA) for the Social

Sciences which includes participation from national fundingagencies (Germany:DFG), (UK:ESRC), (US:NSF) 12 / 27

http://www.icar-project.com/

http://www.icar-project.com/ICAR_News_Issue_One.pdf

http://www.icar-project.com/ICAR_News_Issue_One.pdf


abiliy:ICAR

ICAR: Proof of concept

1. Condon & Revelle (2014) examined the first 60 publiclyavailable items.

2. We are using them here to examine how ability relates todimensions of temperament and of interest.

3. Domains measured and item sources• Temperament items taken from International Personality Item

Pool (IPIP) (Goldberg, 1999) (ipip.ori.org) andsupplemented with other items.

• Ability items have been validated (Condon & Revelle, 2014) aspart of the International Cognitive Ability Resource Project(ICAR-project.org). (ICAR:Ability::IPIP:Temperament)

• Interest items taken from Oregon Vocational Interest Survey(ORVIS) (Pozzebon, Visser, Ashton, Lee & Goldberg, 2010)

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ipip.ori.org

ICAR-project.org


abiliy:ICAR

Structure of sample ICAR 16 items shows a clear 4 factorhierarchical solution ωh = .87

Omega Hierarchical for ICAR Sample Test

LN.07

LN.34

LN.33

LN.58

R3D.03

R3D.08

R3D.04

R3D.06

MR.45

MR.46

MR.55

MR.47

VR.17

VR.04

VR.16

VR.19

LetterNum

0.80.70.60.5

3D Rotate

0.8

0.8

0.7

0.5

Matrices 0.70.70.50.4

Verbal R0.8

0.7

0.6

0.5

g

0.9

0.7

0.9

0.9

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abiliy:ICAR

Structure of ICAR 60 items shows a messier 4 factor hierarchicalsolution ωh = .76

Hierarchical structure of ICAR60 items

VR.18VR.39VR.14VR.17LN.01VR.42VR.19VR.09VR.04VR.16LN.03VR.26VR.36LN.34R3D.07R3D.02R3D.17R3D.24R3D.18R3D.14R3D.19R3D.13R3D.12R3D.11R3D.01R3D.03R3D.21R3D.04R3D.08R3D.15R3D.10R3D.23R3D.09R3D.16R3D.05R3D.22R3D.06R3D.20MR.48MR.46MR.45MR.56MR.53MR.55MR.44MR.47MR.43LN.05LN.33MR.50LN.06LN.07MR.54LN.58LN.35VR.23VR.13VR.31VR.32VR.11

Verbal R

10.90.80.60.60.50.50.50.50.50.40.40.40.3

0.40.30.3-0.3

3D Rotate

0.80.70.70.70.70.70.70.70.70.70.60.60.60.60.60.60.60.60.50.50.50.50.40.4Matrices

0.30.3

0.3

0.60.60.60.60.60.60.60.50.50.50.50.40.40.40.40.40.30.3LetterNum

0.30.30.3

0.3

0.3

0.3

0.3

g

0.8

0.6

1

0.4

15 / 27


Temperament and Interests

Multiple solutions to the dimensionality of temperament

1. Eysenck “Giant 3” (Eysenck, 1994)

2. The “Big 5” (Digman, 1990; Goldberg, 1990)

3. Condon (2014, 2015) examined 696 non-overlapping itemsfrom IPIP:100, IPIP:NEO, IPIP:MSQ, BFAS, EPQ, etc.(Goldberg, 1999; DeYoung, Quilty & Peterson, 2007; Eysenck, Eysenck & Barrett, 1985)

Found meaningful 3, 5, and 15 factor solutions.

4. The Condon 3/5/15 form a heterarchical and non hierarchicalstructure (i.e., lower levels are not cleanly nested in higherlevels.)

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The best items from the 15 scale solution

Table: Sample items from the Short Personality Inventory 15 factorsolution

Each scale has 8-10 itemsSPI Item ItemFear Panic easily. Begin to panic when there is danger.Volatility Get irritated easily. Lose my temper.Outlook Dislike myself. Feel a sense of worthlessness or hopelessness.Compassion Sympathize with others feelings. Am sensitive to the needs of others.Trust Trust others Trust what people say.Easygoing Let things proceed at their own pace. Take things as they come.Industrious Start tasks right away. Get chores done right away.Mach Use others for my own ends. Cheat to get ahead.Impulsivity Act without thinking. Do things without thinking of the consequences.Sociability Am mostly quiet when with other people. Tend to keep in the background on social occasions.Boldness Love dangerous situations. Take risks.Serious Seldom joke around. Am not easily amused.Conventional Don’t like the idea of change. Prefer to stick with things that I know.Intellectual Am quick to understand things. Catch on to things quickly.Open Enjoy thinking about things. Love to reflect on things.

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6 factors of interests

1. 6 factors from the O*NET interest profiler scales (60 items; Rounds,

Su, Lewis & Rivkin, 2010)

2. 8 factor Oregon Vocational Interest Scales (92 items; Pozzebon et al., 2010)

3. Oregon Avocational Interest Scales (199 items; Goldberg, 2010)

4. Formed into 6 scales fitting a “RIASEC” structure (60 items)

Realistic “Like to work with tools and machinery.”Investigative “Would like to do laboratory tests to identify

diseases.”Artistic “Would like to write short stories or novels.”

Social “Would like to help conduct a group therapysession.”

Enterprising “Would like to be the chief executive of a largecompany.”

Clerical “ Would like to keep inventory records”

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Pooled correlations 6= within group or between group correlations

TAI for groups is not the same as TAI for individuals

1. How do occupational groups differ on TAI?• The mean scores for groups allow us to compare the groups• But it is the structure of these group means that are

particularly interesting

2. Overall correlation is a function of within group correlationsand between group correlations.

3. Correlations of aggregate scores rxybg (between groups) 6=aggregate of correlations rxywg (within groups)

4. The overall correlation rxy is a function of the within and thebetween correlationsrxy = etaxwg ∗ etaywg ∗ rxywg + etaxbg ∗ etaybg ∗ rxybg

5. These multi level correlations sometimes lead to what isknown as the Yule-Simpson paradox (Kievit, Frankenhuis, Waldorp &

Borsboom, 2013; Simpson, 1951; Yule, 1903)

• These are independent and useful information.

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Occupational Choice as niche selection

Temperament, Ability, and Interests – within and between groups

1. Examined the factor structure of the TAI scales at the normal,between subjects (across groups) level.

• This produces the normal factor structure of temperament, ofability and of interests

• Can show these correlations as a “heatmap”

2. But when analyzing the structure of the mean scores for eachof 196 occupational groups (minimum size of 75 members),the structure is drastically different.

• Several dimensions of temperament and interests are nownegatively correlated with ability, others are orthogonal

• Can also show these correlations as a “heatmap”

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Subject Level data of 5 personality scales, 6 interests, 4 ability

TAI for employed

ClericalEnterSocialArti

InvestRealVerb3DRotMatrix

LetNumOpIntExt

ConsAgreeNeur

gender

gender

Neur

Agree

Cons

Ext

OpInt

LetNum

Matrix

3DRot

Verb

Real

Invest

Arti

Social

Enter

Clerical

0.02 -0.01 -0.08 0.15 -0.06 -0.09 0.09 0.06 0.08 0.05 0.32 0.28 0.06 0.13 0.42 1

-0.24 -0.12 -0.15 0.07 0.14 0.07 0.06 0.03 0.03 0.04 0.3 0.18 0.18 0.09 1 0.42

0.34 0.03 0.33 0.07 0.14 0.11 -0.05 -0.04 -0.12 -0.09 -0.07 0.09 0.21 1 0.09 0.13

-0.13 0.04 0.06 -0.11 0.01 0.36 0.18 0.17 0.2 0.23 0.29 0.27 1 0.21 0.18 0.06

-0.26 -0.04 -0.11 -0.02 -0.09 0.2 0.21 0.23 0.29 0.28 0.43 1 0.27 0.09 0.18 0.28

-0.56 -0.08 -0.17 -0.07 -0.08 0.04 0.2 0.23 0.27 0.19 1 0.43 0.29 -0.07 0.3 0.32

-0.19 -0.01 -0.09 -0.19 -0.17 0.22 0.9 0.83 0.72 1 0.19 0.28 0.23 -0.09 0.04 0.05

-0.3 -0.05 -0.14 -0.24 -0.18 0.22 0.72 0.71 1 0.72 0.27 0.29 0.2 -0.12 0.03 0.08

-0.19 -0.04 -0.09 -0.15 -0.14 0.15 0.85 1 0.71 0.83 0.23 0.23 0.17 -0.04 0.03 0.06

-0.17 -0.03 -0.06 -0.13 -0.12 0.15 1 0.85 0.72 0.9 0.2 0.21 0.18 -0.05 0.06 0.09

-0.16 -0.16 0.17 0.06 0.12 1 0.15 0.15 0.22 0.22 0.04 0.2 0.36 0.11 0.07 -0.09

0.11 -0.2 0.27 0.12 1 0.12 -0.12 -0.14 -0.18 -0.17 -0.08 -0.09 0.01 0.14 0.14 -0.06

0.18 -0.22 0.26 1 0.12 0.06 -0.13 -0.15 -0.24 -0.19 -0.07 -0.02 -0.11 0.07 0.07 0.15

0.39 -0.03 1 0.26 0.27 0.17 -0.06 -0.09 -0.14 -0.09 -0.17 -0.11 0.06 0.33 -0.15 -0.08

0.27 1 -0.03 -0.22 -0.2 -0.16 -0.03 -0.04 -0.05 -0.01 -0.08 -0.04 0.04 0.03 -0.12 -0.01

1 0.27 0.39 0.18 0.11 -0.16 -0.17 -0.19 -0.3 -0.19 -0.56 -0.26 -0.13 0.34 -0.24 0.02

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

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Group Level data of 15 personality scales, 6 interests, 4 ability

TAI between groups

ClericalEnterSocialArti

InvestRealVerb3DRotMatrix

LetNumOpIntExt

ConsAgreeNeur

gender

gender

Neur

Agree

Cons

Ext

OpInt

LetNum

Matrix

3DRot

Verb

Real

Invest

Arti

Social

Enter

Clerical

-0.09 -0.07 -0.13 0.2 -0.01 -0.02 0.02 0.03 -0.01 -0.02 0.17 0.01 -0.05 -0.12 0.35 1

-0.22 -0.21 -0.29 -0.04 0.12 0.12 0.09 0.09 0.08 0.04 0.2 -0.03 0.1 -0.14 1 0.35

0.5 0.15 0.56 0.11 0.25 -0.11 -0.3 -0.27 -0.32 -0.26 -0.38 -0.15 -0.11 1 -0.14 -0.12

-0.04 0.19 -0.08 -0.42 -0.13 0.43 0.24 0.25 0.29 0.28 0.1 -0.02 1 -0.11 0.1 -0.05

-0.26 -0.21 -0.22 -0.03 -0.29 0.07 0.33 0.39 0.35 0.28 0.3 1 -0.02 -0.15 -0.03 0.01

-0.75 -0.38 -0.59 -0.24 -0.34 0.2 0.35 0.36 0.42 0.28 1 0.3 0.1 -0.38 0.2 0.17

-0.38 -0.07 -0.42 -0.54 -0.41 0.57 0.92 0.88 0.84 1 0.28 0.28 0.28 -0.26 0.04 -0.02

-0.48 -0.25 -0.49 -0.5 -0.49 0.6 0.89 0.89 1 0.84 0.42 0.35 0.29 -0.32 0.08 -0.01

-0.41 -0.19 -0.41 -0.45 -0.39 0.51 0.93 1 0.89 0.88 0.36 0.39 0.25 -0.27 0.09 0.03

-0.44 -0.16 -0.46 -0.48 -0.42 0.51 1 0.93 0.89 0.92 0.35 0.33 0.24 -0.3 0.09 0.02

-0.19 -0.13 -0.13 -0.41 -0.14 1 0.51 0.51 0.6 0.57 0.2 0.07 0.43 -0.11 0.12 -0.02

0.31 -0.09 0.38 0.25 1 -0.14 -0.42 -0.39 -0.49 -0.41 -0.34 -0.29 -0.13 0.25 0.12 -0.01

0.29 -0.21 0.41 1 0.25 -0.41 -0.48 -0.45 -0.5 -0.54 -0.24 -0.03 -0.42 0.11 -0.04 0.2

0.75 0.29 1 0.41 0.38 -0.13 -0.46 -0.41 -0.49 -0.42 -0.59 -0.22 -0.08 0.56 -0.29 -0.13

0.52 1 0.29 -0.21 -0.09 -0.13 -0.16 -0.19 -0.25 -0.07 -0.38 -0.21 0.19 0.15 -0.21 -0.07

1 0.52 0.75 0.29 0.31 -0.19 -0.44 -0.41 -0.48 -0.38 -0.75 -0.26 -0.04 0.5 -0.22 -0.09

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

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Niche selection

1. Occupations differ systematically in intellectual Abilityrequired

2. But they also differ in Interests and Temperament required.

3. A simple two factor solution shows that high ability can tradeoff for low Industry or Conscientiousness and that Boldness(low Anxiety) and Realistic interests differs from high Anxietyand Social interests.

4. We can examine the extent to which this second dimension adifference of gender using factor extension.

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Biplot of a two factor solution to the group level data

-3 -2 -1 0 1 2 3

-3-2

-10

12

3Biplot of TAI scores at group level

MR1

MR2

Fear

Volatility

Enthus

Compassion

Trust

Easygoing

Industry

Mach

Impulsivity

Sociability

Bold

Serious

Habit

Int

Open LetNumMatrix3DRot

Verb

Real

Invest

Arti

Social

EnterClerical

-1.0 -0.5 0.0 0.5 1.0

-1.0

-0.5

0.0

0.5

1.0

24 / 27



Add gender to the extended factor solution of the group data

-3 -2 -1 0 1 2 3

-3-2

-10

12


MR1

MR2

Fear

Volatility

Enthus

Compassion

Trust

Easygoing

Industry

Mach

Impulsivity

Sociability

Bold

Serious

Habit

Int


Verb

Real

Invest

Arti

Social

EnterClerical

gender

-1.0 -0.5 0.0 0.5 1.0

-1.0

-0.5

0.0

0.5

1.0

25 / 27



Biplot of a two factor solution to the group level data

-3 -2 -1 0 1 2 3

-3-2

-10

12


MR1

MR2 Actor

Art Director

Coach and/or Scout

Copy Writer

Editor

Graphic Designer

Musician and/or Singer

Photographer

Producer and/or DirectorPublic Relations Specialist

Writer

Other - ArtistOther - Designer

Other - Entertainer and/or PerformerOther - Media Related Worker

Janitor and/or Cleaner (except Maid and/or Housekeeping Cleaner)

Landscaping and/or Groundskeeping Worker

Maid and/or Housekeeping Cleaner

AccountantAuditor

Budget AnalystBusiness Operations Specialist

Credit Analyst

Financial Analyst

Human Resources and/or Training

Loan Officer

Management Analyst

Personal Financial AdvisorOther - Financial Specialist

Other - Business Worker

Clergy

Counselor - Educational, Vocational, and SchoolCounselor - Mental Health

Probation Officer and/or Correctional Treatment Specialist

Social and Human Service Assistant

Social Worker - Child, Family and/or SchoolSocial Worker - Mental Health and/or Substance Abuse

Other - Community and/or Social Service Specialist

Other - Counselor

Other - Religious WorkerOther - Social Worker

Business Intelligence Analyst

Computer and Information Scientist

Computer Programmer

Computer Security Specialist

Computer Software Engineer

Computer Specialist

Computer Support Specialist

Computer Systems Engineers/Architect

Database AdministratorInformation Technology Project Manager

Network and Computer Systems Administrator

Software Quality Assurance Engineer and/or TesterWeb Developer

Other - Computer Science Worker

Carpenter

Construction Laborer

ElectricianSupervisor/Manager of Construction and/or Extraction Workers

Other - Construction and Related Work

Adult Literacy, Remedial Education, and/or GED Teacher and/or Instructor

Elementary School Teacher (except Special Education)

Graduate Teaching Assistant

Instructional CoordinatorInstructional Designer and/or Technologist

Kindergarten Teacher (except Special Education)Librarian

Library Technician

Middle School Teacher (except Special and Vocational Education)

Postsecondary Teacher - Business

Postsecondary Teacher - Education

Postsecondary Teacher - English Language and/or Literature

Postsecondary Teacher - Psychology

Preschool Teacher (except Special Education)

Secondary School Teacher (except Special and Vocational Education)

Special Education Teacher - Preschool, Kindergarten, and Elementary School

Special Education Teacher - Secondary School

Teacher Assistant

Tutor

Other - Education, Training, or Library WorkerOther - Teacher and/or Instructor

Architect

Civil Engineer

Electrical EngineersMechanical Engineer

Other - Engineer

BaristaBartender

Chef and/or Head Cook

Cook - Fast Food

Cook - Institutional and Cafeteria

Cook - Other

Cook - Restaurant

Cook - Short Order

Dishwasher

Food Preparation Worker

Food Server

Food Service Attendant/Helper

Host/HostessSupervisor/Manager of Food Preparation and Serving Workers

Waiter/Waitress

Other - Food Preparation Worker

Acute Care Nurse

Dental Assistant

Emergency Medical Technician and/or Paramedic

Family and General Practitioner

Home Health Aide

Licensed Practical Nurse and/or Licensed Vocational Nurse

Massage Therapist

Medical and Clinical Laboratory Technician and/or Technologist

Medical Assistant

Medical Records and Health Information Technicians

Nurse Practitioner

Nursing Aid, Orderly and/or Attendant

Pharmacist

Pharmacy Technician

Physical Therapist

Psychiatrist

Radiologic Technologist and/or Technician

Registered Nurse

Surgical TechnologistOther - Health Technologist and/or TechnicianOther - Healthcare Support Worker

Other - Therapist

Automotive Mechanic and/or Service Technician

Electrical and Electronics Installer and/or RepairerOther - Installation, Maintenance, and Repair Worker

Law Clerk

Lawyer

Paralegal and/or Legal Assistant

Other - Legal Worker

Other - Legal Support WorkerBiologists

Psychologist - ClinicalPsychologist - Counseling

Psychologist - Other

Social Science Research Assistant

Other - Social Scientist

Administrative Services Manager

Chief Executive Officer

Computer and Information Systems ManagerFinancial Manager

Food Service Manager

General and Operations Manager

Human Resources Manager

Marketing Manager

Sales ManagerTraining and Development Manager

Other - Manager

Supervisor/Manager of Production Workers

Other - Production Worker

Air Crew Member

InfantrySupervisor/Manager of All Other Tactical Operations Specialists

Other - Military Enlisted Special and Tactical Operations Crew Member and/or Specialist

Other - Military Officer Special and Tactical Operations Leader/Manager

Billing Clerk

Bookkeeping, Accounting, and Auditing Clerks

Customer Service Representative

Data Entry KeyerExecutive Secretary and/or Administrative Assistant

Hotel, Motel, and Resort Desk Clerk

Human Resources AssistantInsurance Claims and/or Policy Processing Clerk

Medical Secretary

Office Clerk, General

Receptionist and/or Information ClerkSecretary

Supervisor/Manager of Office and Administrative Support Workers

Other - Office and Administrative Support Worker

Child Care Worker

Hairdresser, Hairstylist, and/or Cosmetologist

Nanny

Personal and Home Care Aide

Other - Personal Care and Service Worker

Correctional Offices and/or Jailer

Security Guard

Other - Protective Service Worker

Advertising Sales AgentCashierCounter and/or Rental ClerkFinancial Services Sales Agent

Insurance Sales Agent

Real Estate Sales AgentRetail Salesperson

Sales Representative - Services

Sales Representative - Wholesale and ManufacturingSupervisor/Manager of Retail Sales Workers

Supervisors/Manager of Non-Retail Sales Workers

Telemarketer

Other - Sales RepresentativeOther - Sales Worker

Driver/Sales Worker

Laborer - Freight, Stock, and/or Material Moving

Other - Material Moving Worker

Other - Transportation Workers

Fear

Volatility

Enthus

Compassion

Trust

Easygoing

Industry

Mach

Impulsivity

Sociability

Bold

Serious

Habit

Int


Verb

Real

Invest

Arti

Social

EnterClerical

gender

-1.0 -0.5 0.0 0.5 1.0

-1.0

-0.5

0.0

0.5

1.0

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Summary and Conclusions

1. Ability, temperament and interests all provide usefulinformation about human personality.

2. Intellectual and Personality development is the process ofexperiencing and choosing niches.

3. When we describe the intellectual requirements of aprofession, we should not ignore that appropriate interests andtemperaments guide occupational choice.

4. We need to consider appetites along with aptitudes.

5. For more information and for these slides go tohttp://personality-project.org/sapa.html

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http://personality-project.org/sapa.html


Bouchard, T. (1997). Experience producing drive theory: howgenes drive experience and shape personality. Acta Paediatrica,86(S422), 60–64.

Condon, D. M. (2014). An organizational framework for thepsychological individual differences: Integrating the affective,cognitive, and conative domains. PhD thesis, NorthwesternUniversity.

Condon, D. M. (2015). The many little items of “big five”measures: Hierarchy, heterarchy, and predictive utility inpersonality structure. Long Beach, California. Society ofPersonality and Social Psychology.

Condon, D. M. & Revelle, W. (2014). The International CognitiveAbility Resource: Development and initial validation of apublic-domain measure. Intelligence, 43, 52–64.

Deary, I. (2008). Why do intelligent people live longer? Nature,456(7219), 175–176.

27 / 27


DeYoung, C. G., Quilty, L. C., & Peterson, J. B. (2007). Betweenfacets and domains: 10 aspects of the big five. Journal ofPersonality and Social Psychology, 93(5), 880–896.

Digman, J. M. (1990). Personality structure: Emergence of thefive-factor model. Annual Review of Psychology, 41, 417–440.

Eysenck, H. J. (1994). The big five or the giant three: Criteria fora paradigm. In C. F. Halverson, G. A. Kohnstamm, & R. P.Martin (Eds.), The developing structure of temperament andpersonality from infancy to adulthood (pp. 37–51). Hillsdale,N.J.: Lawrence Erlbaum Associates.

Eysenck, S. B. G., Eysenck, H. J., & Barrett, P. (1985). A revisedversion of the psychoticism scale. Personality and IndividualDifferences, 6(1), 21 – 29.

Goldberg, L. R. (1990). An alternative “description ofpersonality”: The big-five factor structure. Journal ofPersonality and Social Psychology, 59(6), 1216–1229.

27 / 27


Goldberg, L. R. (1999). A broad-bandwidth, public domain,personality inventory measuring the lower-level facets of severalfive-factor models. In I. Mervielde, I. Deary, F. De Fruyt, &F. Ostendorf (Eds.), Personality psychology in Europe, volume 7(pp. 7–28). Tilburg, The Netherlands: Tilburg University Press.

Goldberg, L. R. (2010). Personality, demographics and selfreported acts: the development of avocational interest scalesfrom estimates of the mount time spent in interest relatedactivities. In C. Agnew, D. Carlston, W. Graziano, & J. Kelly(Eds.), Then a miracle occurs: Focusing on the behavior insocial psychological theory and research (pp. 205–226). NewYork, NY: Oxford University Press.

Gottfredson, L. S. (1997). Why g matters: The complexity ofeveryday life. Intelligence, 24(1), 79 – 132.

Hayes, K. (1962). Genes, drives, and intellect. PsychologicalReports (Monograph Supplement 2), 10, 299–342.

27 / 27


Johnson, W. (2010). Extending and testing tom bouchard’sexperience producing drive theory. Personality and IndividualDifferences, 49(4), 296 – 301. Collected works from theFestschrift for Tom Bouchard, June 2009: A tribute to a vibrantscientific career.

Kelly, E. L. & Fiske, D. W. (1950). The prediction of success inthe VA training program in clinical psychology. AmericanPsychologist, 5(8), 395 – 406.

Kelly, E. L. & Fiske, D. W. (1951). The prediction of performancein clinical psychology. Ann Arbor, Michigan: University ofMichigan Press.

Kievit, R. A., Frankenhuis, W. E., Waldorp, L. J., & Borsboom, D.(2013). Simpson’s paradox in psychological science: a practicalguide. Frontiers in Psychology, 4(513), 1–14.

Lord, F. M. (1955). Estimating test reliability. Educational andPsychological Measurement, 15, 325–336.

27 / 27


Pozzebon, J. A., Visser, B. A., Ashton, M. C., Lee, K., &Goldberg, L. R. (2010). Psychometric characteristics of apublic-domain self-report measure of vocational interests: Theoregon vocational interest scales. Journal of PersonalityAssessment, 92(2), 168–174.

Roberts, B. W., Kuncel, N. R., Shiner, R., Caspi, A., & Goldberg,L. R. (2007). The power of personality: The comparativevalidity of personality traits, socioeconomic status, and cognitiveability for predicting important life outcomes. Perspectives onPsychological Science, 2(4), 313–345.

Rounds, J., Su, R., Lewis, P., & Rivkin, D. (2010). O* NET R©interest profiler short form psychometric characteristics:Summary.

Simpson, E. H. (1951). The interpretation of interaction incontingency tables. Journal of the Royal Statistical Society.Series B (Methodological), 13(2), 238–241.

27 / 27


Yule, G. U. (1903). Notes on the theory of association ofattributes in statistics. Biometrika, 2(2), 121–134.

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