facts 2017 - · pdf filein the new survey, we collected data for 229 festival editions [of...

FACTS 2017by the female:pressure Trouble Makers

Version: 1.1 / Date: August 31, 2017 / Authors: The Trouble Makers

female:pressureFACTS 2017

Table of Contents:

1. Introduction 3 2. Methods 4 Aims and Objectives Data Collection Data Analysis

3. Results 5 Gender Proportions of Festival Acts Gender Proportions Over Time GenderProportionsforDifferentRegions Gender Proportions by Country Gender Proportions by Festival Size

4. Discussion 10 SummaryoftheResults Comparison With Other Studies StrengthsandLimitationsoftheSurvey QuestionsthatRemainUnanswered SuggestionsforFestivalOrganisers,ArtisticDirectors,Artists

5. Acknowledgements 14

6. Appendices 15 GenderProportionsforallRegions Gender Proportions for all Countries Gender Proportions for all Festivals


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The female:pressure FACTS survey is a biennial project undertaken byvolunteer members of the female:pressure network.

Starting in 2013 [https://femalepressure.wordpress.com/facts-graphic/], the FACTS survey was initiated to address and quantify the deficit in equal opportunity and visibility for female artists in the electronic music scene. The result of the 2013 FACTS survey indicated that barely 10% of artists listed in festival line-ups worldwide are female--and opened up an international discussion about the state of women in electronic music.

In 2015 [https://femalepressure.wordpress.com/facts-survey2015/], we conducted the sur-vey anew. Although the inequities within the industry had become a popular topic of debate since the 2013 edition, the 2015 FACTS survey demonstrated the continued lack of women on music festival line-ups.

While this phenomenon is receiving more media coverage today than ever before, we believe that measuring trends through the FACTS survey is necessary to understand the true state of inequity in the electronic music scene and to hold decision-makers accountable within the industry.

We embarked on FACTS 2017 with the goal of assessing the female-male-mixed [i.e., acts comprised of both male and female artists] gender proportions among artists performing at music festivals in the years 2015, 2016 and the first half of 2017 with a focus on the year 2016. Even though we included many new festivals for this year’s edition, our emphasis re-mains on the regions of Europe and North America. In gathering data from these years, we aim to assess both time trends from 2012 to 2017 and country specific female-male-mixed gender proportions. With 229 festival editions, it is the most comprehensive FACTS survey yet.

For this year’s FACTS survey, our team asked each one of the included festivals to participate by submitting their own numbers. Twelve of the 133 festivals responded and filled out our data collection form.

In surveying more festivals in more countries than ever before, we may see the extent to which inequity is a systemic issue. Structural sexism perpetuates inequality by creating barriers and disincentives for women, which limits women’s success in the arts to genres and media aligned with the status quo.*

Although progress is certainly being made with respect to the visibility of women in the industry since the 2013 FACTS survey, we are reminded that mere coverage or visibility can not sub-stitute for systematic change. Cultural change is indeed happening, as we see overt sexism and prejudices “called out”, but structural change is necessary to truly addressing underrepre-sentation.** As musicologist Elizabeth Keenan argues, solutions must simultaneously address gaps in education and access for female artists.

Our FACTS survey, like the female:pressure network, is the result of grassroots activism--con-ducted independently from any for-profit organization and without external funding. The 2017 edition of the survey was undertaken by six core volunteers, nicknamed the “Trouble Makers”, with the aid of seventeen helpers.

*https://femalepressure.wordpress.com/2017/08/22/womens-representation-in-music/**https://www.residentadvisor.net/news.aspx?id=39316

1. INTRODUCTION

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Aims and Objectives

The aim of the present survey was to assess the gender distribution among artists performing at electronic music festivals around the world.

Specifically, we wanted to- assess the female-male-mixed gender proportions among artists performing at electronic music festivals taking place in the year 2015 up to mid-year of 2017 with focus on the year 2016- assess time trends in these female-male-mixed gender proportions from 2012 to 2017- assess differences in these female-male-mixed gender proportions for regions and countries.

Data Collection

Data was collected for all countries worldwide with no restrictions. However, the focus was on festivals taking place in Europe and North America. We used a standardised online form to collect single sets of data for each festival edition.

The survey’s focus is on electronic music. Festivals were included if they feature a mainly elec-tronic music program. However, once a festival was included into the survey, all acts were count-ed [regardless of their musical genre]. Potential festivals were searched for online.

The search was performed on [but was not limited to] the following sites:https://www.festicket.com/magazine/top-techno-festivals-europe/https://www.festicket.com/magazine/top-20-music-festivals-Europe/https://www.festicket.com/magazine/top-10-electronic-music-festivals-uk/http://icasnetwork.org http://ecasnetwork.orghttps://www.residentadvisor.net/festivals.aspxhttp://shapeplatform.eu/festival/https://www.theguardian.com/travel/2017/apr/03/10-best-music-festivals-europe-spain-france-croatiahttps://www.residentadvisor.net/features/2939

For each festival, the following data were collected:- Name of festival- Country- City- Date- Number of female acts in the line-up- Number of male acts in the line-up- Number of mixed [female/male] acts in the line-up- Number of unidentified acts in the line-up

The number of acts were counted per slot of stage time. For example:Dasha Rush & Donato Dozzy back-to-back DJ-set: categorized as 1 mixed act.Electric indigo [audio] & Thomas Wagensommerer [video] a/v set: categorized as 1 mixed act.Lucrecia Dalt & Gudrun Gut live: categorized as 1 female act.

‘Acts’ include musical and visual artists [if listed in the line-up], with the exception of CTM [Ger-many] which also includes panel and discourse acts.

2. METHODS

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For the purpose of this survey, gender data is distinguished and collected only as male or female. Transgender artists are assigned according to their chosen gender. If the gender of a trans person is difficult to decide, the person should be listed according to thepronoun s/he uses for themselves. In addition, articles about the artist might be checked to judge, if this person is generally referred to as she or he. Cis male artists with female aliases/monikers were regarded as male artists. In cases which could not be resolved, artists were assigned ‘un-identified’.

Data was provided by Trouble Makers members, by female:pressure members, or by festival or-ganisers. Festival organisers were emailed a standardized letter explaining the background and the purpose of the survey along with an invitation to enter their festival data into a short online form. To minimize data entry errors, we were able to verify about one third of all festival editions by double data entry.

Data Analysis

Data was analysed descriptively. Female, male, mixed, and unidentified gender proportions are presented numerically and graphically: overall, by year, country, and by region. In addition, trends in time for specific festivals [with data for several time points] are presented. Mean [i.e. average] percentages are calculated by adding the number of acts for the specific gender divided by the total number of acts [times 100] for each festival. Due to rounding, numbers presented throughout this document may not add up precisely to 100%. Festivals were also categorized and analysed by size [defined by the total number of acts]. To see if gender proportions depend on the size of the festival we used the number of total acts to categorize festivals into 3 groups: small [up to 25 acts], medium [26-50 acts], or large [more than 50 acts], as well as into 5 more refined groups: very small [less than 20 acts], small [20-29 acts], medium [30-45 acts], large [46-90 acts], or very large [more than 90 acts].

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3. RESULTSIn the new survey, we collected data for 229 festival editions [of 133 different festivals] from 2015 to mid-year 2017. The focus was on festivals in 2016 with 116 festival editions and on 2017 with 48 festival editions [s. Table 1]. In total, the present and all previous surveys comprised, we col-lected data for 322 festival editions [182 festivals] from 2012 to June 30, 2017.

Table 1. Number of festivals [n,%] by year

Small [up to 25 acts] 107 14.9% 77.2% 7.8% 0.1%Medium [26-50 acts] 101 14.0% 80.2% 5.4% 0.4%Large [more than 50 acts] 114 13.2% 78.8% 7.2% 0.8%Total 322 13.5% 78.9% 6.9% 0.7%

Festival Size Number ofFestivals

Very Small [less than 20 acts] 77 16.9% 76.1% 6.8% 0.2%Small [20-29 acts] 52 14.7% 77.3% 7.8% 0.2%Medium [30-45 acts] 101 14.0% 80.2% 5.4% 0.4%Large [46-90 acts] 62 14.9% 78.2% 6.1% 0.8%Very Large [more than 50 acts] 65 12.4% 79.3% 7.5% 0.8%Total 322 13.5% 78.9% 6.9% 0.7%

Number ofFestivals

Female Male Mixed UnidentifiedFestival Size

N %

2012 31 9.62013 18 5.62014 44 13.72015 65 20.22016 116 36.02017 [mid year] 48 14.9

2012 31 9.2% 81.5% 9.0% 0.3%2013 18 10.9% 84.3% 4.5% 0.3%2014 44 10.7% 81.8% 6.6% 0.9%2015 65 13.5% 78.1% 7.4% 1.0%2016 116 14.3% 78.0% 7.0% 0.7%2017 [mid year] 48 18.9% 75.4% 5.4% 0.3%Total 322 13.5% 78.9% 6.9% 0.7%

Number ofFestivals Female Male Mixed Unidentified

Austria 19 18.4% 74.5% 6.8% 0.3% 14 19.2% 73.8% 6.7% 0.3%Belgium 13 6.6% 86.0% 7.4% 0.0% 10 13.0% 77.9% 9.1% 0.0%Canada 11 17.2% 76.8% 4.7% 1.3% 7 22.1% 72.4% 3.9% 1.6%France 22 11.1% 83.0% 5.9% 0.0% 16 10.4% 84.1% 5.5% 0.0%Germany 40 14.8% 74.2% 10.0% 1.0% 25 16.3% 72.6% 9.8% 1.3%Japan 11 6.4% 88.1% 5.4% 0.0% 8 6.9% 88.2% 4.9% 0.0%Mexico 16 9.1% 88.2% 2.4% 0.3% 16 9.1% 88.2% 2.4% 0.3%Netherlands 16 11.7% 83.6% 4.6% 0.1% 14 13.9% 81.2% 4.8% 0.1%Spain 40 11.9% 79.0% 8.4% 0.7% 23 14.0% 76.3% 9.0% 0.7%UK 19 11.2% 79.0% 7.0% 2.8% 12 11.0% 76.4% 9.7% 2.9%USA 40 14.1% 81.0% 4.6% 0.4% 36 14.8% 80.1% 4.7% 0.4%Total 247 13.2% 79.2% 6.9% 0.7% 181 14.4% 78.0% 6.8% 0.8%

Country 2012 to mid-year 2017 2015 to mid-year 2017Number ofFestivals Female Male Mixed Unidentified Number of

Festivals Female Male Mixed Unidentified

Female Male Mixed Unidentified


In total, festivals from 34 countries were included with 233 festivaleditions [72.4%] from Europe and 67 [20.8%] from North America. 98 festivals wereincluded only once in the data collection, while for 46 festivals data was collected fortwo time points. 23, 12 and 3 festivals provided data for 3, 4, or 5 time points, respectively.

The mean [i.e. average] festival size was 58.9 acts with a minimum of 4 and a maximum of 726 act per festival. In total, 18956 acts are included in the present survey. For the current data 2015 to mid-year 2017, festivals had a mean of 57.6 acts [minimum 4, maximum 726] and a total of 13197 acts included.

Gender Proportions of Festival Acts

Overall, for festivals in 2012 to mid-year 2017, 14% of all acts were female acts, 79% were male, 7% were mixed acts, and 1% were unidentified [i.e. acts where the gender could not be assured], s. Figure 1. For the newly collected data comprising festivals from 2015 to mid-year of 2017, there were 15% female acts and 78% ‚ 7% , and 1% male, mixed and unidentified acts, respectively.

Figure 1. Gender proportions of festival acts [left: 2012 to mid-year 2017, right: 2015 to mid-year 2017]

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Figure 2. Female artists [in %] over time Figure 3. Female, male and mixed artists [in %] over time

********** This is �gure 1 (left part) in the Results document ***************

Female14%

Male79% Mixed

7%

Unidentified1%

FP colours#3

75.4%

18.9%

5.4%

MALEFEMALEMIXEDUNIDENTIFIED

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********** This is �gure 4 (left part) in the Results document ***************

SUM of Mean_percent by GenderRegion=Europe

Europe

Female14%

Male78%

Mixed8%

Unidentified1%

********** This is �gure 4 (right part) in the Results document ***************SUM of Mean_percent by Gender

Region=North America

NorthAmerica

Female14%

Male82%

Mixed4%

Unidentified1%

********** This is �gure 6 in the Results document ***************SUM of Mean_percent by Gender

Gender Female Male Mixed Unidentified

Large [more than 50 acts]Medium [26-50 acts]Small [up to 25 acts]

********** This is �gure 7 in the Results document ***************SUM of Mean_percent by Gender

Very Large [more than 90 acts]Large [46-90 acts]Medium [30-45 acts]Small [20-29 acts]Very Small [less than 20 acts]


Fem

ale

Acts

[%]

0.0

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90.0

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Festival Size [number of acts]

0 100 200 300 400 500 600 700 800

Female proportions by festival size (total number of acts) [2012 to mid-year 2017]

****************** This is �gure 8 in the results document **********************

Mea

n Fe

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e Ac

ts (%

)

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2012 2013 2014 2015 2016 mid-year 2017


Mea

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ons

(%)

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2012 2013 2014 2015 2016 mid-year 2017

Mean female/male/mixed proportions over time 2012 to mid-year 2017


Female Male Mixed

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Female15%

Male78% Mixed

7%

Unidentified1%

Gender Proportions Over Time

Over time [2012 to mid-year 2017], there was a slight increase in the number of femaleartists [Figure 2] and a slight decrease in the number of male artists [Figure 3 and Table 2].




Number ofFestivals


N %

2012 31 9.62013 18 5.62014 44 13.72015 65 20.22016 116 36.02017 [mid year] 48 14.9

2012 31 9.2% 81.5% 9.0% 0.3%2013 18 10.9% 84.3% 4.5% 0.3%2014 44 10.7% 81.8% 6.6% 0.9%2015 65 13.5% 78.1% 7.4% 1.0%2016 116 14.3% 78.0% 7.0% 0.7%2017 [mid year] 48 18.9% 75.4% 5.4% 0.3%Total 322 13.5% 78.9% 6.9% 0.7%






Table 2. Female, male, mixed and unidentified acts in % over time

For festivals with data for 4 or more years, we assessed changes over time per festival. Figure 4 shows the percentage of female acts separately for each festival. There seems to be an over-all trend towards an increase in female acts for several festivals. Results for further festivals are shown in Appendix 3.

Figure 4. Female festival acts [in %] for festivals with data for 4 or more years

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Europe

Female14%

Male78%

Mixed8%

Unidentified1%

NorthAmerica

Female14%

Male82%

Mixed4%

Unidentified1%




Number ofFestivals


N %

2012 31 9.62013 18 5.62014 44 13.72015 65 20.22016 116 36.02017 [mid year] 48 14.9

2012 31 9.2% 81.5% 9.0% 0.3%2013 18 10.9% 84.3% 4.5% 0.3%2014 44 10.7% 81.8% 6.6% 0.9%2015 65 13.5% 78.1% 7.4% 1.0%2016 116 14.3% 78.0% 7.0% 0.7%2017 [mid year] 48 18.9% 75.4% 5.4% 0.3%Total 322 13.5% 78.9% 6.9% 0.7%






Gender proportions seem quite different when looking at various counties. For example, for the overall reults 2012 to mid-year 2017 festivals in Belgium and Japan have the lowest female per-centages [less than 7%] while festivals in Canada and Austria are highest [over 17%]. Table 3 shows the proportions of female, male, mixed, and unidentified acts by country for countries with 10 or more festival editions in 2012 to mid-year 2017, as well as the current data for the same festivals. Results for further countries are shown in Appendix 2.

Table 3. Proportion of acts by country [2012 to mid-year 2017 and 2015 to mid-year 2017]

GenderProportionsforDifferentRegions

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Comparing European and North American festival data, the same rates of female actswere seen [14%, s. Figure 5]. Results for further regions are shown in Appendix 1.

Figure 5. Gender rates for European [left] and North American [right] festivals [2012 to mid-year 2017]

Gender Proportions by Country


Large [more than 50 acts]Medium [26-50 acts]Small [up to 25 acts]

Very Large [more than 90 acts]Large [46-90 acts]Medium [30-45 acts]Small [20-29 acts]Very Small [less than 20 acts]




Number ofFestivals


N %

2012 31 9.62013 18 5.62014 44 13.72015 65 20.22016 116 36.02017 [mid year] 48 14.9

2012 31 9.2% 81.5% 9.0% 0.3%2013 18 10.9% 84.3% 4.5% 0.3%2014 44 10.7% 81.8% 6.6% 0.9%2015 65 13.5% 78.1% 7.4% 1.0%2016 116 14.3% 78.0% 7.0% 0.7%2017 [mid year] 48 18.9% 75.4% 5.4% 0.3%Total 322 13.5% 78.9% 6.9% 0.7%






We also wanted to see, if gender proportions depend on the size of the festival.Lacking visitor numbers, we used the number of total acts to categorize festivals into three groups as well as more refined into five groups. The graph on the left in Figure 6 / Table 4 show that the number of female acts is similar across the three categories, while the graph on the right side of Figure 6 / Table 5 shows five categories.

Figure 6. Female, male, mixed and unidentified acts by festival size in three and five categories[2012 to mid-year 2017]

Table 4. Female, male, mixed and unidentified acts by festival size in three categories [2012 to mid-year 2017]

Table 5. Female, male, mixed and unidentified acts by festival size in five categories [2012 to mid-year 2017]

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Number ofFestivals


N %

2012 31 9.62013 18 5.62014 44 13.72015 65 20.22016 116 36.02017 [mid year] 48 14.9

2012 31 9.2% 81.5% 9.0% 0.3%2013 18 10.9% 84.3% 4.5% 0.3%2014 44 10.7% 81.8% 6.6% 0.9%2015 65 13.5% 78.1% 7.4% 1.0%2016 116 14.3% 78.0% 7.0% 0.7%2017 [mid year] 48 18.9% 75.4% 5.4% 0.3%Total 322 13.5% 78.9% 6.9% 0.7%






Gender Proportions by Festival Size


Figure 7 shows the percentage of female acts for each festival by the size of the respective festival [festival size is defined by the total number of acts] with extremesof 0% women as well as 100% women.

Figure 7. Female acts [in %] by festival size [defined by the total number of acts, 2012 to mid-year 2017]

SummaryoftheResults

In our present survey, assessing festivals acts from 2015 to mid-year 2017, we found that 15% of all acts were female while 78% were male. We saw that, although the rate of female acts rose slightly over the years, there is still an enormous gap between female and male artists appearing on stage.

Comparison With Other Studies

Thump [a subsidiary of Vice] conducted a similar survey focusing specifically on electronic music festivals in 2016: https://thump.vice.com/en_us/article/qkazzq/2016-electronic-music-festivals-gender-breakdownThe scope of this survey was much smaller than the FACTS survey: Thump tallied only 24 festivals [all taking place in the first half of 2016] and they did not account for mixed acts, instead counting all mixed acts as female.

The Huffington Post also conducted a music festival gender parity survey in 2016, though they considered a broader range of genres:http://data.huffingtonpost.com/music-festivalsAgain, the scope of this survey was much smaller than the FACTS survey: 10 festivals’ line-ups over 2012-2016 [50 editions total]. However, like the FACTS survey, Huffington was very transpar-ent about their methodology: http://data.huffingtonpost.com/music-festivals/methodology

4. DISCUSSION

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Pitchfork also conducted a similar survey in 2017, though the scopewas multi-genre and included only 23 festivals, for a total of 996 acts counted: http://pitchfork.com/features/festival-report/10059-are-music-festival-lineups-getting-worse/

All three of these surveys came up with very similar percentages: festival line-ups on average in-clude only 12%-14% female acts, and on average only 10%-12% mixed acts.

In 2016, Deutscher Kulturrat [an umbrella organisation of German cultural assemblies] published a very comprehensive study about the job market development for women in culture and media in Germany. The report comprises data mostly retrieved through administrative bodies, covers a time span of 20 years and a variety of sectors. For the music sector, the study does not draw any distinction between musical genres but rather between kinds of occupation. The analysis is based on the amount of insured persons and their income. Thus, a direct comparison with our results for an international electronic music scene and the representation of women in festival line-ups does not make much sense. However, it is an interesting example of a gender survey even if its aims differ from our own.https://www.kulturrat.de/wp-content/uploads/2016/12/Frauen-in-Kultur-und-Medien.pdf[http://www.dw.com/en/how-germany-is-boosting-womens-careers-in-culture-and-the-media/a-39729533]

StrengthsandLimitationsoftheSurvey

In the course of conducting the survey, it became quite obvious that counting female, male and mixed acts is not as simple as it seems at first glance. Thus, it was important that we make clear guidelines for how to count as accurately and consistently as possible. Due to the grassroots character of the whole undertaking and the amount of helpers and contributors involved, these guidelines [which you can read in the “Methods” section] were often partly overlooked or may-be also misunderstood. Some not-so-easy-to-answer questions were raised. For example, how should we count an act who is announced under a single, easy to identify artist name but who actually performed with other musicians, singers, or visual artists with different genders who are not listed in the line-up? Even if you were present at the performance, you might not have seen everybody on stage. Such incidents often depend on insider information to be aware of them at all and lead to varying results for the very same festival edition.

All data collected is based on the unit “act”, not the single artists on stage/number of persons an act consists of. Assuming there is no systematic gender difference in the number of persons in male or female acts would yield a similar gender proportion regardless if acts or persons are counted. If this assumption holds, however, is unclear.

Another, very frequent phenomenon was the presence of different information about the same festival edition in different media. Resident Advisor would show different numbers of acts than the Facebook event, for example. Festival programs are updated frequently and various versions of them can be found online. Quite a few websites or single web pages disappear or substantially change over time which makes it difficult to find out who played if we were trying to evaluate num-bers submitted a year or two ago.

On the other hand, it is a huge advantage to have so many helpers who are directly involved in the scene we examine and thus know many artist names anyway and can be a lot quicker assigning them to one of the three gender categories we had so far.

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We would have liked to verify the data more than we did.We reviewed 78 of 229 festival editions for the current survey butlacked time and womanpower to re-count more editions. This is mainly due to thewhole project being based on voluntary work without any financial support. Nevertheless,even if some numbers might be less accurate than we aimed for, the overall result would onlybe affected to a minor degree. In addition, we do not assume that any potential errors in counting the festival acts are systematic but would rather be random. Thus, errors should not systematically bias the results in one direction but even each other out.

Another possible factor that would result in distorted results is “selection bias”. For example, or-ganisers of festivals with a higher number of female acts might be more willing to take part in the survey; this would lead to an overestimation of female acts. A solution to this bias is to try to count all existing electronic music festivals. In addition, since data was provided by festivals organizers for only 23 of the 229 [10%] festival editions for 2015-2017, and 90% of data was assessed by the “Trouble Makers” group, we don’t consider this type of bias to be relevant.

QuestionsthatRemainUnanswered

Up to now, we did not take a very important factor into account: Does the festival receive public funds? We think that with receiving grants from governmental authorities, i.e. tax money, the ob-ligation to program a fair and diverse line-up is even more pressing. We would be interested to compare the factors “public funds” with “gender proportion”. There is reason to believe that line-ups of festivals who receive such funds feature more women as these cultural grants and subsi-dies are often subject to regulations concerning gender equality. A publicly accessible resource where information about the financing of festivals can be retrieved would be extremely helpful for assessment of this issue.

It is obvious that electronic music festival line-ups in at least Europe and North America are domi-nated by white people. This is particularly striking as electronic dance music originates from black and latinx communities. Without these DJs, artists, and audiences of colour we would not even be able to examine what we are examining now. We are very interested in surveys that have a look into the overall quota of people of colour invited to play at such festivals. And we are specifically interested in the representation of women* of colour in this scene.

We are also wondering if the gender and number of festival bookers, curators, and/or program-mers affect the gender balance of line-ups. Is it a single curator who might act as an impresario or is it a team of curators? Do female bookers book more female artists? Or could it have a contrary effect that women responsible for a festival’s program need to over-fulfill a “relevance” criteria and thus book the most hyped and therefore mostly male artists?

A study like the aforementioned “Frauen-in-Kultur-und-Medien” by Deutscher Kulturrat which in-vestigates the income development of professionals in culture and media would be extremely helpful to complement our surveys if it distinguished musical genres and, ideally, compared sev-eral countries.

We would like to see and eventually also contribute to a code of conduct: a guideline for best practice for festivals to accommodate the societal and cultural implications that their programs, advertising, and publications produce. We think it is never and has never been “just about the mu-sic”. There is much more to a festival than that: the achievement of relevance, economic success, social factors--many times on a very personal level--the advancement of a genre [“adventurous music”], political factors and/or other agendas.

We also would like to put more thought into how we categorize non-binary artists, which the cur-rent male/female categories do not account for.

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SuggestionsforFestivalOrganisers,ArtisticDirectors,Artists

The results of our FACTS survey show that little has changed in terms of the representation of women in festival programs. But there are festivals which can be seen asbest-practice examples to increase the diversity in line-ups: VIA Festival [Pittsburgh, USA],Intonal [Malmö, Sweden], Norbergfestival [Norberg, Sweden], Hyperreality [Vienna, Austria] and CTM [Berlin, Germany], for example.

It can be supposed that every single festival has a special set of circumstances and that those circumstances have an effect on the representation of women in their line-ups. In its current form, our study is not capable of answering the question of which characteristics make the difference between gender parity and disparity. Still, we want to offer some thoughts about what we think might be helpful in making line-ups more diverse in the future:

First of all, pursuant of an ethical and political agenda that acknowledges the importance of equal rights and meets concerns about the discrimination against all those who are not white and male artists: Believe in a multi-faceted and heterogeneous electronic music scene. Believe in a less capitalistic approach to your listeners and support a more performance-oriented music culture.

Book more women, non-binary people and people of colour. If you believe they won’t fit your crowd and/or won´t bring in enough money, invest in good press work, install or support under-ground stages and generally promote a vibe of inclusiveness for your event. Network and col-laborate with more booking agencies that have a diverse roster of artists and inform yourself about and/or connect with festivals around the world that make an effort to include equal numbers of women and strive for overall diversity in their line-ups.

On the organisational level: Install a mixed-gender team to program your festival’s line-up. If you are interested in making a change and representing more women, non-binary and people of color in your festival program--thereby reflecting the state of the art in electronic music--make, for example, a public call for participation and describe how you want electronic music to be repre-sented within your festival. We could therefore imagine that festivals reserve a part of their line-up for those artists who get booked through a call which invites especially female artists, non-binary artists and artists of colour.

Support your local underground scene, connect with record dealers and music journalists who are basically experts in the field.

If you have the capacity, host a workshop and discourse program and invite especially women, people of colour and newcomers as panelists and participants. Topics might range from gear, music production, mastering to publishing, music promotion and other music business-related issues. By supporting workshops for music production and DJing, people get connected and informed about the scene so that they can support each other and maybe get booked for your festival the next time. We also suppose that the relationship between artists and festival promot-ers will change then. The workshops and discourse program can be funded in a variety of ways, from ticket sales to donations and fundings [e.g. socio-cultural programs].

When looking at the working conditions of your festival, be aware of the special needs for women and parents in general which could mean installing a system of cooperative and safe child-care for artists’ and staff’s kids.

Initiatives like the Clubcommission Berlin [http://www.clubcommission.de/dokumente/Infos_in_English.html], who want to represent the gateway between clubs, promoters, industry and cultural policy play-ers; engage in the needs and perspectives of the different protagonists in club and festival

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5. ACKNOWLEDGEMENTSCore Survey Team

Angelika Lepper [Utting am Ammersee]Meg Wilhoite [San Francisco]Michelle Endo [Oakland]Stephanie Roll [Berlin]Susanne Kirchmayr [Vienna]Tanja Ehmann [Berlin]

GraphicDesign

CO/RE Studio [Berlin] Moira Letby [London]

Data Collection Helpers

Aiko Okamoto [Berlin]Alex Alexopoulos [Paris]Anke Müller [Saarbrücken]Bianca Ludewig [Berlin]Caro Churchill [Manchester]Corina MacDonald [Montreal]Daniela Seitz [Berlin]Ece Özel [Istanbul]Evgenia Nedosekina [Moscow]Evren Da Conceiçåo [Vienna]Franziska Plückhan [Berlin]Iolanda Casino [Barcelona]Janina Schütz [Berlin]Maureen Schipper [London]Nina Kardec [Paris]Olivia Louvel [London]Sarah Martinus [Berlin]

and the many individuals who sent data using our online form!

14

culture, and could function as an umbrella organisation for festivals,too, to collaboratively work out guidelines which could be developed into a certification.If a festival successfully follows these guidelines, they can promote the festival with the logoof this certification.

With focus on the artists, we have a few more suggestions: Connect yourself with local and/or global networks and resources for women and non-binary artists, you can find a lot of them on the female:pressure website.

Some male artists already show solidarity with their female colleagues and refuse to play if there are no or not enough women on the line-up. We think this is a great strategy that makes promoters and curators question their policies!

Asia 12 7.4% 87.7% 4.9% 0.0%Caribbean 1 14.7% 77.3% 7.8% 0.0%Europe 233 14.0% 80.2% 5.4% 0.7%North America 67 14.9% 78.2% 6.1% 0.5%Pacific 3 12.4% 79.3% 7.5% 0.0%South America 6 12.4% 79.3% 7.5% 0.0% Total 322 13.5% 78.9% 6.9% 0.7%

Region

Argentina 12 7.4% 87.7% 4.9% 0.0%Australia 1 14.7% 77.3% 7.8% 0.0%Austria 233 14.0% 80.2% 5.4% 0.7%Belgium 67 14.9% 78.2% 6.1% 0.5%Brazil 3 12.4% 79.3% 7.5% 0.0%Canada 6 12.4% 79.3% 7.5% 0.0%Croatia 3 3.9% 93.0% 1.6% 1.6%Cuba 1 9.4% 81.3% 9.4% 0.0%Czech Republic 8 13.2% 80.3% 6.1% 0.4%Denmark 7 16.4% 69.0% 14.3% 10.3%Finland 1 5.3% 76.7% 18.0% 0.0%France 22 11.1% 83.0% 5.9% 0.0%Georgia 3 2.2% 97.8% 0.0% 0.0%Germany 40 14.8% 74.2% 10.0% 1.0%Greece 1 0.0% 100.0% 0.0% 1.0%Hungary 2 16.7% 76.9% 6.4% 0.0%Japan 11 6.4% 88.1% 5.4% 0.0%Latvia 2 18.4% 75.5% 6.1% 0.0%Mexico 16 9.1% 88.2% 2.4% 0.3%Netherlands 16 11.7% 83.6% 2.4% 0.1%Norway 5 20.8% 69.0% 10.2% 0.0%Poland 3 15.7% 77.2% 6.7% 0.3%Portugal 2 3.7% 91.3% 1.8% 3.2%Romania 3 25.0% 72.9% 2.1% 0.0%Russia 6 6.7% 88.1% 5.2% 0.0%Singapore 1 16.7% 83.3% 0.0% 0.0%Slovakia 2 8.8% 88.2% 2.9% 0.0%Slovenia 1 0.0% 88.9% 11.1% 0.0%Spain 40 11.9% 79.0% 8.4% 0.7%Sweden 9 33.8% 60.2% 5.5% 0.5%Switzerland 4 11.6% 82.9% 5.0% 0.6%UK 19 11.2% 79.0% 7.0% 2.8%USA 40 14.1% 81.0% 4.6% 0.4%Ukraine 2 15.5% 82.8% 0.0% 1.7%Total 322 13.5% 78.9% 6.9% 0.7%

Number ofFestivals Female Male Mixed UnidentifiedCountry


6. APPENDICESAppendix 1: Gender proportions for all regions [2012 to mid-year 2017]Appendix 2: Gender proportions for all countries [2012 to mid-year 2017]Appendix 3: Gender proportions for all festivals [by year]

Appendix 1: Gender proportions for all regions [2012 to mid-year 2017]

14 15


Appendix 2: Gender proportions for all countries [2012 to mid-year 2017]

Asia 12 7.4% 87.7% 4.9% 0.0%Caribbean 1 14.7% 77.3% 7.8% 0.0%Europe 233 14.0% 80.2% 5.4% 0.7%North America 67 14.9% 78.2% 6.1% 0.5%Pacific 3 12.4% 79.3% 7.5% 0.0%South America 6 12.4% 79.3% 7.5% 0.0% Total 322 13.5% 78.9% 6.9% 0.7%

Region

Argentina 12 7.4% 87.7% 4.9% 0.0%Australia 1 14.7% 77.3% 7.8% 0.0%Austria 233 14.0% 80.2% 5.4% 0.7%Belgium 67 14.9% 78.2% 6.1% 0.5%Brazil 3 12.4% 79.3% 7.5% 0.0%Canada 6 12.4% 79.3% 7.5% 0.0%Croatia 3 3.9% 93.0% 1.6% 1.6%Cuba 1 9.4% 81.3% 9.4% 0.0%Czech Republic 8 13.2% 80.3% 6.1% 0.4%Denmark 7 16.4% 69.0% 14.3% 10.3%Finland 1 5.3% 76.7% 18.0% 0.0%France 22 11.1% 83.0% 5.9% 0.0%Georgia 3 2.2% 97.8% 0.0% 0.0%Germany 40 14.8% 74.2% 10.0% 1.0%Greece 1 0.0% 100.0% 0.0% 1.0%Hungary 2 16.7% 76.9% 6.4% 0.0%Japan 11 6.4% 88.1% 5.4% 0.0%Latvia 2 18.4% 75.5% 6.1% 0.0%Mexico 16 9.1% 88.2% 2.4% 0.3%Netherlands 16 11.7% 83.6% 2.4% 0.1%Norway 5 20.8% 69.0% 10.2% 0.0%Poland 3 15.7% 77.2% 6.7% 0.3%Portugal 2 3.7% 91.3% 1.8% 3.2%Romania 3 25.0% 72.9% 2.1% 0.0%Russia 6 6.7% 88.1% 5.2% 0.0%Singapore 1 16.7% 83.3% 0.0% 0.0%Slovakia 2 8.8% 88.2% 2.9% 0.0%Slovenia 1 0.0% 88.9% 11.1% 0.0%Spain 40 11.9% 79.0% 8.4% 0.7%Sweden 9 33.8% 60.2% 5.5% 0.5%Switzerland 4 11.6% 82.9% 5.0% 0.6%UK 19 11.2% 79.0% 7.0% 2.8%USA 40 14.1% 81.0% 4.6% 0.4%Ukraine 2 15.5% 82.8% 0.0% 1.7%Total 322 13.5% 78.9% 6.9% 0.7%

Number ofFestivals Female Male Mixed UnidentifiedCountry



Appendix 3: Gender proportions for all festivals [by year]

16

3hd Festival

4GB

50 Years of MinimalismAbstrasensionAlfa Future PeopleApparitions Festival

AquasellaArs ElectronicaAVA

Awakenings Festival

Bass CoastBerlin Atonal

Berlin FestivalBerlin Music WeekBoom FestivalBozar

BPM Festival

BY:LARMc/o popCarnaval de Bahidorá

CasiMiniFestChance of RainClick

CommunikeyComunite

Crosstown Rebels Day Zero

Crssd Festival

CTM

CynetartDay for NightDecibel Festival

Dekmantel Festival Amsterdam

Dekmantel Festival São PauloDekmantel Festival Tokyo AprilDekmantel Festival Tokyo NovemberDekmantel LondonDekmantel SelectorsDesert Hearts Spring

Dirty Bird Campout

donaufestival

Dour Festivale_may FestivalEkkofestivalenElectric Daisy Carnival New YorkElectric Daisy Carnival OrlandoElectric Spring

Electric Spring Huddersfield

Electron Festival

Electronica En Abril

ElevateEufònicFascinoma FestivalFlow FestivalFORM Arcosanti

frameworks festivalFree RotationFurther FutureFusion

FutureEverything

FYF FestGeometry of NowGRM - AkousmaGRM - Live electroniqueGuteZeit Festival

Heart of Noise

Holy ShipHyperrealityHyte Berlin - NYE WeekI Love Techno

I Love Techno Europe

ICAS FestivalIgloofest

III Bienal Música HojeInsomnia

intonal

kontrA2punktKRAA! FestivalKraak Festival

Krake Festival

L.E.V. Festival

L'EstranyLabyrinthLapsus Festival

LEM Festival

Lente Kabinet

Les Femmes s’en MêlentLes Siestes Electroniques Paris

Les Siestes Electroniques Toulouse

Lightning in a Bottle

LostTheoryLove Saves the Day

LoveboxLunchmeat

MáchácMAGNETIC FestivalMaintenant

Mamby on the Beach

Manana CubaMeakusmaMelt!

MEM

MetamorphoseMira Festival

Modern FestivalMonegrosMoogfest

Movement Detroit

music unlimitedmusic we'd like to hearMusikprotokoll

Mutek Barcelona

Mutek Montreal

Mutek MX

MysterylandNation of GondwanaNeopop FestivalNew Forms Festival

NEXT FestivalNorbergfestival

Nördik Impakt

Novas Frequencias

Nuits Sonores

Off_HerziosOortredersOpen MusicOutlookPirate StationPitchfork Music Festival ChicagoPop-KulturPoprevoPrimavera Sound

Q-O2 festival the other the self

Rainbow Disco Club

Rewire

Rokolectiv

RoskildeSchiev

SCOPEScopitoneShe Makes Noise

Sirilo Music FestivalSkanu Mezs

SKIFSochi Music WeekendSónar

Sónar Sound TokyoSonicaSonne Mond Sterne

SonoritiesSound and MusicSPOT

springfestival

StörungStrichka Festival

STRP BIËNNALE

Supersonic FestivalSymbiosis GatheringSynCussionTaicoClub

The Bunker x DekmantelThe Chosen Few DjsTime Warp

Time Warp Argentina

Time Warp USATodaysArt

Together Festival

TransmissionTrenelenburgUltrahang Fest

Unsound Adelaide

Unsound Krakow

Unsound TbilisiUP FestivalUrban Art FormsVIA Festival

Volt Festival

Voltt FestivalWax Treatment Africa SpecialWeather FestivalWhat The FestivalXibalba FestivalZoukoutTotal

Number ofActs Female Male Mixed UnidentifiedFestival

2015201620162017201220162016201620172014201220162017201520162017201620152016201420122014201220152016201520162013201220152016201720142016201520162017201320162017201620172016201720152016201720142013201620162015201420152016201420172016201620162016201620172015201620152016201220122012201220122016201720152016201720132016201720142013201520162017201420162014201620122015201620172013201420162015201620122015201620132016201720172017201620172015201620172017201720142012201420162014201520152016201720152015201620142015201620172014201420152016201520162014201320152016201420142015201620172014201520162016201720132015201620152016201420162017201320162017201620152016201220142014201420152016201620172016201620152016201220142015201620122016201420162014201620172015201620172013201220162015201620152016201720142013201520162012201420152016201620142012201620142014201520162012201420152016201420152016201520162017201320142016201620162016201620162015201520162017201420152016201620172016201720152016201720152015201620162016201520162016201520162016201620152016201720142013201220162015201620132012201520122016201720132014201620172015201720122016201720152016201720122016201620152016201720152016201520152016201220152016201720142014201520162015201620122015201620122012201420132015201620122013201620122014201720162014

19 47.4% 47.4% 5.3% 0.0% 23 47.8% 43.5% 8.7% 0.0% 32 3.1% 96.9% 0.0% 0.0% 46 0.0% 100.0% 0.0% 0.0% 9 44.4% 55.6% 0.0% 0.0% 25 0.0% 100.0% 0.0% 0.0% 41 7.3% 92.7% 0.0% 0.0% 32 3.1% 96.9% 0.0% 0.0% 31 3.2% 93.5% 3.2% 0.0% 56 8.9% 89.3% 1.8% 0.0%130 24.6% 73.1% 2.3% 0.0% 27 7.4% 85.2% 7.4% 0.0% 44 15.9% 72.7% 4.5% 6.8%110 10.0% 86.4% 3.6% 0.0%103 6.8% 90.3% 2.9% 0.0%112 15.2% 83.0% 1.8% 0.0% 17 17.6% 82.4% 0.0% 0.0% 70 4.3% 90.0% 5.7% 0.0% 89 16.9% 75.3% 7.9% 0.0% 67 3.0% 92.5% 4.5% 0.0% 87 13.8% 75.9% 10.3% 0.0%229 16.2% 72.1% 11.8% 0.0%171 2.9% 90.6% 2.3% 4.1% 24 4.2% 83.3% 12.5% 0.0% 26 15.4% 80.8% 3.8% 0.0%152 5.3% 94.1% 0.7% 0.0%377 9.3% 88.9% 1.1% 0.8%134 21.6% 68.7% 9.7% 0.0% 82 17.1% 65.9% 17.1% 0.0% 21 14.3% 76.2% 9.5% 0.0% 30 3.3% 80.0% 16.7% 0.0% 36 16.7% 77.8% 5.6% 0.0% 6 16.7% 66.7% 16.7% 0.0% 52 17.3% 76.9% 3.8% 1.9% 34 17.6% 70.6% 5.9% 5.9% 33 12.1% 57.6% 30.3% 0.0% 17 29.4% 52.9% 17.6% 0.0% 22 13.6% 81.8% 4.5% 0.0% 34 17.6% 82.4% 0.0% 0.0% 40 12.5% 85.0% 2.5% 0.0% 12 8.3% 91.7% 0.0% 0.0% 12 8.3% 91.7% 0.0% 0.0% 41 7.3% 92.7% 0.0% 0.0% 45 8.9% 86.7% 4.4% 0.0%146 22.6% 73.3% 4.1% 0.0%187 32.1% 58.3% 9.6% 0.0%198 42.9% 53.5% 2.5% 1.0%101 14.9% 76.2% 8.9% 0.0%181 9.9% 84.5% 3.9% 1.7%13 30.8% 53.8% 15.4% 0.0%69 13.0% 75.4% 11.6% 0.0%131 15.3% 84.0% 0.8% 0.0%145 12.4% 82.1% 5.5% 0.0%103 4.9% 95.1% 0.0% 0.0%23 13.0% 87.0% 0.0% 0.0%80 2.5% 96.3% 1.3% 0.0%54 20.4% 79.6% 0.0% 0.0%33 3.0% 97.0% 0.0% 0.0%16 18.8% 81.3% 0.0% 0.0%10 0.0% 100.0% 0.0% 0.0%71 7.0% 93.0% 0.0% 0.0%37 5.4% 91.9% 0.0% 2.7%41 4.9% 92.7% 2.4% 0.0%35 5.7% 88.6% 5.7% 0.0%35 2.9% 94.3% 2.9% 0.0%39 12.8% 69.2% 17.9% 0.0%49 8.2% 71.4% 18.4% 2.0%232 2.2% 90.5% 7.3% 0.0%18 50.0% 5.6% 44.4% 0.0%29 3.4% 86.2% 10.3% 0.0%81 7.4% 87.7% 4.9% 0.0%57 1.8% 94.7% 3.5% 0.0%33 30.3% 54.5% 15.2% 0.0%13 53.8% 46.2% 0.0% 0.0%16 25.0% 62.5% 0.0% 12.5%20 10.0% 50.0% 40.0% 0.0%14 21.4% 64.3% 14.3% 0.0%15 6.7% 93.3% 0.0% 0.0%95 21.1% 74.7% 4.2% 0.0%71 5.6% 87.3% 4.2% 2.8%99 12.1% 82.8% 5.1% 0.0%97 6.2% 87.6% 6.2% 0.0%13 7.7% 84.6% 7.7% 0.0%12 0.0% 100.0% 0.0% 0.0%10 30.0% 70.0% 0.0% 0.0%16 25.0% 68.8% 6.3% 0.0%44 13.6% 84.1% 2.3% 0.0%14 14.3% 71.4% 14.3% 0.0%41 7.3% 90.2% 2.4% 0.0%133 5.3% 76.7% 18.0% 0.0%26 26.9% 57.7% 15.4% 0.0%32 21.9% 71.9% 6.3% 0.0%37 29.7% 62.2% 8.1% 0.0%9 11.1% 88.9% 0.0% 0.0% 88 13.6% 75.0% 1.1% 10.2%61 6.6% 83.6% 9.8% 0.0%552 10.9% 71.0% 14.9% 3.3%726 10.9% 72.7% 14.0% 2.3%251 9.6% 69.3% 21.1% 0.0%27 11.1% 81.5% 3.7% 3.7%21 19.0% 66.7% 14.3% 0.0%22 4.5% 90.9% 4.5% 0.0%52 15.4% 78.8% 5.8% 0.0%30 6.7% 80.0% 13.3% 0.0%10 20.0% 80.0% 0.0% 0.0%10 0.0% 90.0% 10.0% 0.0%10 0.0% 100.0% 0.0% 0.0%14 0.0% 100.0% 0.0% 0.0%28 7.1% 89.3% 3.6% 0.0%26 7.7% 84.6% 7.7% 0.0%25 24.0% 76.0% 0.0% 0.0%142 9.2% 89.4% 1.4% 0.0%78 47.4% 44.9% 7.7% 0.0%28 7.1% 92.9% 0.0% 0.0%37 0.0% 97.3% 2.7% 0.0%36 5.6% 91.7% 2.8% 0.0%21 0.0% 100.0% 0.0% 0.0%24 0.0% 100.0% 0.0% 0.0%35 17.1% 74.3% 8.6% 0.0%118 16.9% 79.7% 1.7% 1.7%109 35.8% 60.6% 3.7% 0.0%71 23.9% 70.4% 5.6% 0.0%73 8.2% 91.8% 0.0% 0.0%34 26.5% 67.6% 5.9% 0.0%26 30.8% 61.5% 7.7% 0.0%22 18.2% 59.1% 22.7% 0.0%26 26.9% 61.5% 11.5% 0.0%38 31.6% 55.3% 10.5% 2.6%41 51.2% 41.5% 7.3% 0.0%9 0.0% 66.7% 33.3% 0.0%17 5.9% 88.2% 5.9% 0.0%13 15.4% 61.5% 23.1% 0.0%22 4.5% 81.8% 13.6% 0.0%48 18.8% 70.8% 10.4% 0.0%49 16.3% 81.6% 2.0% 0.0%42 14.3% 83.3% 2.4% 0.0%37 10.8% 89.2% 0.0% 0.0%20 5.0% 95.0% 0.0% 0.0%30 13.3% 86.7% 0.0% 0.0%21 4.8% 85.7% 9.5% 0.0%12 8.3% 75.0% 16.7% 0.0%16 0.0% 100.0% 0.0% 0.0%17 17.6% 82.4% 0.0% 0.0%11 18.2% 81.8% 0.0% 0.0%15 6.7% 93.3% 0.0% 0.0%22 9.1% 68.2% 22.7% 0.0%29 6.9% 79.3% 13.8% 0.0%29 3.4% 93.1% 3.4% 0.0%26 19.2% 76.9% 3.8% 0.0%26 84.6% 0.0% 15.4% 0.0%10 10.0% 90.0% 0.0% 0.0%8 0.0% 75.0% 25.0% 0.0%12 25.0% 66.7% 8.3% 0.0%13 7.7% 84.6% 7.7% 0.0%12 16.7% 66.7% 16.7% 0.0%72 11.1% 80.6% 8.3% 0.0%105 13.3% 72.4% 14.3% 0.0%126 1.6% 98.4% 0.0% 0.0%124 4.0% 83.9% 10.5% 1.6%101 13.9% 80.2% 5.9% 0.0%166 11.4% 75.9% 7.2% 5.4%36 27.8% 72.2% 0.0% 0.0%38 26.3% 68.4% 5.3% 0.0%22 13.6% 68.2% 18.2% 0.0%38 7.9% 78.9% 10.5% 2.6%64 6.3% 92.2% 1.6% 0.0%10 0.0% 100.0% 0.0% 0.0%29 31.0% 69.0% 0.0% 0.0%37 29.7% 64.9% 5.4% 0.0%42 14.3% 81.0% 4.8% 0.0%61 16.4% 78.7% 4.9% 0.0%32 9.4% 81.3% 9.4% 0.0%66 91.0% 84.8% 9.1% 0.0%120 10.8% 80.8% 8.3% 0.0%121 14.9% 80.2% 5.0% 0.0%59 8.5% 81.4% 10.2% 0.0%72 9.7% 80.6% 9.7% 0.0%23 26.1% 43.5% 30.4% 0.0%17 41.2% 52.9% 5.9% 0.0%20 5.0% 90.0% 5.0% 0.0%32 12.5% 78.1% 9.4% 0.0%50 6.0% 88.0% 6.0% 0.0%21 4.8% 95.2% 0.0% 0.0%41 7.3% 92.7% 0.0% 0.0%114 25.4% 70.2% 4.4% 0.0%88 34.1% 56.8% 9.1% 0.0%143 7.0% 90.9% 0.7% 1.4%124 12.9% 83.9% 1.6% 1.6%113 9.7% 85.8% 4.4% 0.0%77 10.4% 88.3% 1.3% 0.0%28 21.4% 64.3% 14.3% 0.0%10 10.0% 20.0% 70.0% 0.0%69 23.2% 72.5% 4.3% 0.0%51 23.5% 68.6% 7.8% 0.0%17 11.8% 76.5% 11.8% 0.0%31 12.9% 87.1% 0.0% 0.0%25 28.0% 64.0% 8.0% 0.0%27 7.4% 88.9% 3.7% 0.0%24 4.2% 91.7% 4.2% 0.0%77 10.4% 80.5% 1.3% 7.8%81 18.5% 72.8% 8.6% 0.0%56 7.1% 82.1% 10.7% 0.0%104 7.7% 86.5% 5.8% 0.0%49 8.2% 89.8% 2.0% 0.0%64 12.5% 81.3% 6.3% 0.0%109 10.1% 85.3% 1.8% 2.8%36 11.1% 83.3% 5.6% 0.0%48 6.3% 93.8% 0.0% 0.0%38 28.9% 65.8% 5.3% 0.0%54 13.0% 79.6% 1.9% 5.6%17 11.8% 88.2% 0.0% 0.0% 72 41.7% 56.9% 1.4% 0.0%64 42.2% 46.9% 10.9% 0.0%74 16.2% 83.8% 0.0% 0.0%83 30.1% 62.7% 6.0% 1.2%44 2.3% 93.2% 4.5% 0.0%51 7.8% 84.3% 7.8% 0.0%50 6.0% 80.0% 14.0% 0.0%43 27.9% 65.1% 7.0% 0.0%39 17.9% 76.9% 5.1% 0.0%181 5.5% 87.3% 7.2% 0.0%157 10.2% 84.1% 5.7% 0.0%161 11.8% 83.9% 4.3% 0.0%167 7.2% 87.4% 5.4% 0.0%17 17.6% 82.4% 0.0% 0.0%9 0.0% 100.0% 0.0% 0.0%9 0.0% 88.9% 11.1% 0.0%61 4.9% 82.0% 6.6% 6.6%8 12.5% 87.5% 0.0% 0.0%44 22.7% 63.6% 13.6% 0.0%71 33.8% 45.1% 19.7% 1.4%17 5.9% 94.1% 0.0% 0.0%197 10.2% 69.5% 15.7% 4.6%156 7.7% 83.3% 9.0% 0.0%192 13.5% 73.4% 13.0% 0.0%145 9.0% 74.5% 14.5% 2.1%8 50.0% 50.0% 0.0% 0.0%4 50.0% 25.0% 25.0% 0.0%23 4.3% 91.3% 4.3% 0.0%24 8.3% 91.7% 0.0% 0.0%61 24.6% 63.9% 11.5% 0.0%74 18.9% 68.9% 10.8% 1.4%17 17.6% 76.5% 5.9% 0.0%16 31.3% 68.8% 0.0% 0.0%15 26.7% 73.3% 0.0% 0.0%169 17.2% 73.4% 9.5% 0.0%19 21.1% 73.7% 5.3% 0.0%17 17.6% 64.7% 17.6% 0.0%11 9.1% 81.8% 9.1% 0.0%42 14.3% 81.0% 4.8% 0.0%4 75.0% 0.0% 25.0% 0.0%6 100.0% 0.0% 0.0% 0.0%18 5.6% 94.4% 0.0% 0.0%27 25.9% 70.4% 3.7% 0.0%22 9.1% 81.8% 9.1% 0.0%17 17.6% 64.7% 17.6% 0.0%14 0.0% 100.0% 0.0% 0.0%123 13.8% 83.7% 2.4% 0.0%124 11.3% 83.9% 4.8% 0.0%126 21.4% 73.8% 4.8% 0.0%142 9.2% 83.1% 7.7% 0.0%64 3.1% 90.6% 6.3% 0.0%47 8.5% 89.4% 2.1% 0.0%9 0.0% 88.9% 11.1% 0.0%91 5.5% 91.2% 3.3% 0.0%137 5.1% 90.5% 4.4% 0.0%61 16.4% 82.0% 1.6% 0.0%30 10.0% 90.0% 0.0% 0.0%190 15.8% 66.8% 17.4% 0.0%121 16.5% 67.8% 15.7% 0.0%119 8.4% 89.9% 0.8% 0.8%47 8.5% 87.2% 4.3% 0.0%74 2.7% 90.5% 5.4% 1.4%21 9.5% 90.5% 0.0% 0.0%30 13.3% 83.3% 0.0% 3.3%28 17.9% 82.1% 0.0% 0.0%47 4.3% 87.2% 8.5% 0.0%64 35.9% 59.4% 4.7% 0.0%113 7.1% 88.5% 4.4% 0.0%16 12.5% 87.5% 0.0% 0.0%12 33.3% 50.0% 16.7% 0.0%35 5.7% 80.0% 14.3% 0.0%33 12.1% 84.8% 3.0% 0.0%23 4.3% 82.6% 13.0% 0.0%25 0.0% 84.0% 16.0% 0.0%7 14.3% 85.7% 0.0% 0.0%27 11.1% 88.9% 0.0% 0.0%40 7.5% 92.5% 0.0% 0.0%41 9.8% 90.2% 0.0% 0.0%41 12.2% 87.8% 0.0% 0.0%16 0.0% 100.0% 0.0% 0.0%17 0.0% 100.0% 0.0% 0.0%17 5.9% 88.2% 5.9% 0.0%38 15.8% 76.3% 7.9% 0.0%31 29.0% 58.1% 12.9% 0.0%198 6.1% 88.9% 5.1% 0.0%71 14.1% 84.5% 1.4% 0.0%26 23.1% 76.9% 0.0% 0.0%32 21.9% 78.1% 0.0% 0.0%11 0.0% 100.0% 0.0% 0.0%27 0.0% 85.2% 7.4% 7.4%41 9.8% 82.9% 7.3% 0.0%37 24.3% 70.3% 5.4% 0.0%12 8.3% 75.0% 16.7% 0.0%12 16.7% 66.7% 16.7% 0.0%9 0.0% 100.0% 0.0% 0.0%103 13.6% 78.6% 6.8% 1.0%114 24.6% 67.5% 7.9% 0.0%95 7.4% 87.4% 5.3% 0.0%15 6.7% 93.3% 0.0% 0.0%14 0.0% 100.0% 0.0% 0.0%50 2.0% 94.0% 4.0% 0.0%49 42.9% 49.0% 8.2% 0.0%22 50.0% 40.9% 9.1% 0.0%18 27.8% 66.7% 5.6% 0.0%19 42.1% 57.9% 0.0% 0.0%37 2.7% 94.6% 2.7% 0.0%31 0.0% 96.8% 3.2% 0.0%36 5.6% 94.4% 0.0% 0.0%112 8.9% 86.6% 4.5% 0.0%17 23.5% 70.6% 5.9% 0.0%30 16.7% 83.3% 0.0% 0.0%18956 13.5% 78.9% 6.9% 0.7%

16 17


3hd Festival

4GB



Awakenings Festival



BPM Festival



CommunikeyComunite


Crssd Festival

CTM




Dirty Bird Campout

donaufestival



Electron Festival




FutureEverything


Heart of Noise





intonal


Krake Festival

L.E.V. Festival


LEM Festival

Lente Kabinet





LoveboxLunchmeat


Mamby on the Beach


MEM



Movement Detroit


Mutek Barcelona

Mutek Montreal

Mutek MX



Nördik Impakt

Novas Frequencias

Nuits Sonores



Rainbow Disco Club

Rewire

Rokolectiv

RoskildeSchiev






springfestival


STRP BIËNNALE



Time Warp Argentina


Together Festival


Unsound Adelaide

Unsound Krakow


Volt Festival



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19 47.4% 47.4% 5.3% 0.0% 23 47.8% 43.5% 8.7% 0.0% 32 3.1% 96.9% 0.0% 0.0% 46 0.0% 100.0% 0.0% 0.0% 9 44.4% 55.6% 0.0% 0.0% 25 0.0% 100.0% 0.0% 0.0% 41 7.3% 92.7% 0.0% 0.0% 32 3.1% 96.9% 0.0% 0.0% 31 3.2% 93.5% 3.2% 0.0% 56 8.9% 89.3% 1.8% 0.0%130 24.6% 73.1% 2.3% 0.0% 27 7.4% 85.2% 7.4% 0.0% 44 15.9% 72.7% 4.5% 6.8%110 10.0% 86.4% 3.6% 0.0%103 6.8% 90.3% 2.9% 0.0%112 15.2% 83.0% 1.8% 0.0% 17 17.6% 82.4% 0.0% 0.0% 70 4.3% 90.0% 5.7% 0.0% 89 16.9% 75.3% 7.9% 0.0% 67 3.0% 92.5% 4.5% 0.0% 87 13.8% 75.9% 10.3% 0.0%229 16.2% 72.1% 11.8% 0.0%171 2.9% 90.6% 2.3% 4.1% 24 4.2% 83.3% 12.5% 0.0% 26 15.4% 80.8% 3.8% 0.0%152 5.3% 94.1% 0.7% 0.0%377 9.3% 88.9% 1.1% 0.8%134 21.6% 68.7% 9.7% 0.0% 82 17.1% 65.9% 17.1% 0.0% 21 14.3% 76.2% 9.5% 0.0% 30 3.3% 80.0% 16.7% 0.0% 36 16.7% 77.8% 5.6% 0.0% 6 16.7% 66.7% 16.7% 0.0% 52 17.3% 76.9% 3.8% 1.9% 34 17.6% 70.6% 5.9% 5.9% 33 12.1% 57.6% 30.3% 0.0% 17 29.4% 52.9% 17.6% 0.0% 22 13.6% 81.8% 4.5% 0.0% 34 17.6% 82.4% 0.0% 0.0% 40 12.5% 85.0% 2.5% 0.0% 12 8.3% 91.7% 0.0% 0.0% 12 8.3% 91.7% 0.0% 0.0% 41 7.3% 92.7% 0.0% 0.0% 45 8.9% 86.7% 4.4% 0.0%146 22.6% 73.3% 4.1% 0.0%187 32.1% 58.3% 9.6% 0.0%198 42.9% 53.5% 2.5% 1.0%101 14.9% 76.2% 8.9% 0.0%181 9.9% 84.5% 3.9% 1.7%13 30.8% 53.8% 15.4% 0.0%69 13.0% 75.4% 11.6% 0.0%131 15.3% 84.0% 0.8% 0.0%145 12.4% 82.1% 5.5% 0.0%103 4.9% 95.1% 0.0% 0.0%23 13.0% 87.0% 0.0% 0.0%80 2.5% 96.3% 1.3% 0.0%54 20.4% 79.6% 0.0% 0.0%33 3.0% 97.0% 0.0% 0.0%16 18.8% 81.3% 0.0% 0.0%10 0.0% 100.0% 0.0% 0.0%71 7.0% 93.0% 0.0% 0.0%37 5.4% 91.9% 0.0% 2.7%41 4.9% 92.7% 2.4% 0.0%35 5.7% 88.6% 5.7% 0.0%35 2.9% 94.3% 2.9% 0.0%39 12.8% 69.2% 17.9% 0.0%49 8.2% 71.4% 18.4% 2.0%232 2.2% 90.5% 7.3% 0.0%18 50.0% 5.6% 44.4% 0.0%29 3.4% 86.2% 10.3% 0.0%81 7.4% 87.7% 4.9% 0.0%57 1.8% 94.7% 3.5% 0.0%33 30.3% 54.5% 15.2% 0.0%13 53.8% 46.2% 0.0% 0.0%16 25.0% 62.5% 0.0% 12.5%20 10.0% 50.0% 40.0% 0.0%14 21.4% 64.3% 14.3% 0.0%15 6.7% 93.3% 0.0% 0.0%95 21.1% 74.7% 4.2% 0.0%71 5.6% 87.3% 4.2% 2.8%99 12.1% 82.8% 5.1% 0.0%97 6.2% 87.6% 6.2% 0.0%13 7.7% 84.6% 7.7% 0.0%12 0.0% 100.0% 0.0% 0.0%10 30.0% 70.0% 0.0% 0.0%16 25.0% 68.8% 6.3% 0.0%44 13.6% 84.1% 2.3% 0.0%14 14.3% 71.4% 14.3% 0.0%41 7.3% 90.2% 2.4% 0.0%133 5.3% 76.7% 18.0% 0.0%26 26.9% 57.7% 15.4% 0.0%32 21.9% 71.9% 6.3% 0.0%37 29.7% 62.2% 8.1% 0.0%9 11.1% 88.9% 0.0% 0.0% 88 13.6% 75.0% 1.1% 10.2%61 6.6% 83.6% 9.8% 0.0%552 10.9% 71.0% 14.9% 3.3%726 10.9% 72.7% 14.0% 2.3%251 9.6% 69.3% 21.1% 0.0%27 11.1% 81.5% 3.7% 3.7%21 19.0% 66.7% 14.3% 0.0%22 4.5% 90.9% 4.5% 0.0%52 15.4% 78.8% 5.8% 0.0%30 6.7% 80.0% 13.3% 0.0%10 20.0% 80.0% 0.0% 0.0%10 0.0% 90.0% 10.0% 0.0%10 0.0% 100.0% 0.0% 0.0%14 0.0% 100.0% 0.0% 0.0%28 7.1% 89.3% 3.6% 0.0%26 7.7% 84.6% 7.7% 0.0%25 24.0% 76.0% 0.0% 0.0%142 9.2% 89.4% 1.4% 0.0%78 47.4% 44.9% 7.7% 0.0%28 7.1% 92.9% 0.0% 0.0%37 0.0% 97.3% 2.7% 0.0%36 5.6% 91.7% 2.8% 0.0%21 0.0% 100.0% 0.0% 0.0%24 0.0% 100.0% 0.0% 0.0%35 17.1% 74.3% 8.6% 0.0%118 16.9% 79.7% 1.7% 1.7%109 35.8% 60.6% 3.7% 0.0%71 23.9% 70.4% 5.6% 0.0%73 8.2% 91.8% 0.0% 0.0%34 26.5% 67.6% 5.9% 0.0%26 30.8% 61.5% 7.7% 0.0%22 18.2% 59.1% 22.7% 0.0%26 26.9% 61.5% 11.5% 0.0%38 31.6% 55.3% 10.5% 2.6%41 51.2% 41.5% 7.3% 0.0%9 0.0% 66.7% 33.3% 0.0%17 5.9% 88.2% 5.9% 0.0%13 15.4% 61.5% 23.1% 0.0%22 4.5% 81.8% 13.6% 0.0%48 18.8% 70.8% 10.4% 0.0%49 16.3% 81.6% 2.0% 0.0%42 14.3% 83.3% 2.4% 0.0%37 10.8% 89.2% 0.0% 0.0%20 5.0% 95.0% 0.0% 0.0%30 13.3% 86.7% 0.0% 0.0%21 4.8% 85.7% 9.5% 0.0%12 8.3% 75.0% 16.7% 0.0%16 0.0% 100.0% 0.0% 0.0%17 17.6% 82.4% 0.0% 0.0%11 18.2% 81.8% 0.0% 0.0%15 6.7% 93.3% 0.0% 0.0%22 9.1% 68.2% 22.7% 0.0%29 6.9% 79.3% 13.8% 0.0%29 3.4% 93.1% 3.4% 0.0%26 19.2% 76.9% 3.8% 0.0%26 84.6% 0.0% 15.4% 0.0%10 10.0% 90.0% 0.0% 0.0%8 0.0% 75.0% 25.0% 0.0%12 25.0% 66.7% 8.3% 0.0%13 7.7% 84.6% 7.7% 0.0%12 16.7% 66.7% 16.7% 0.0%72 11.1% 80.6% 8.3% 0.0%105 13.3% 72.4% 14.3% 0.0%126 1.6% 98.4% 0.0% 0.0%124 4.0% 83.9% 10.5% 1.6%101 13.9% 80.2% 5.9% 0.0%166 11.4% 75.9% 7.2% 5.4%36 27.8% 72.2% 0.0% 0.0%38 26.3% 68.4% 5.3% 0.0%22 13.6% 68.2% 18.2% 0.0%38 7.9% 78.9% 10.5% 2.6%64 6.3% 92.2% 1.6% 0.0%10 0.0% 100.0% 0.0% 0.0%29 31.0% 69.0% 0.0% 0.0%37 29.7% 64.9% 5.4% 0.0%42 14.3% 81.0% 4.8% 0.0%61 16.4% 78.7% 4.9% 0.0%32 9.4% 81.3% 9.4% 0.0%66 91.0% 84.8% 9.1% 0.0%120 10.8% 80.8% 8.3% 0.0%121 14.9% 80.2% 5.0% 0.0%59 8.5% 81.4% 10.2% 0.0%72 9.7% 80.6% 9.7% 0.0%23 26.1% 43.5% 30.4% 0.0%17 41.2% 52.9% 5.9% 0.0%20 5.0% 90.0% 5.0% 0.0%32 12.5% 78.1% 9.4% 0.0%50 6.0% 88.0% 6.0% 0.0%21 4.8% 95.2% 0.0% 0.0%41 7.3% 92.7% 0.0% 0.0%114 25.4% 70.2% 4.4% 0.0%88 34.1% 56.8% 9.1% 0.0%143 7.0% 90.9% 0.7% 1.4%124 12.9% 83.9% 1.6% 1.6%113 9.7% 85.8% 4.4% 0.0%77 10.4% 88.3% 1.3% 0.0%28 21.4% 64.3% 14.3% 0.0%10 10.0% 20.0% 70.0% 0.0%69 23.2% 72.5% 4.3% 0.0%51 23.5% 68.6% 7.8% 0.0%17 11.8% 76.5% 11.8% 0.0%31 12.9% 87.1% 0.0% 0.0%25 28.0% 64.0% 8.0% 0.0%27 7.4% 88.9% 3.7% 0.0%24 4.2% 91.7% 4.2% 0.0%77 10.4% 80.5% 1.3% 7.8%81 18.5% 72.8% 8.6% 0.0%56 7.1% 82.1% 10.7% 0.0%104 7.7% 86.5% 5.8% 0.0%49 8.2% 89.8% 2.0% 0.0%64 12.5% 81.3% 6.3% 0.0%109 10.1% 85.3% 1.8% 2.8%36 11.1% 83.3% 5.6% 0.0%48 6.3% 93.8% 0.0% 0.0%38 28.9% 65.8% 5.3% 0.0%54 13.0% 79.6% 1.9% 5.6%17 11.8% 88.2% 0.0% 0.0% 72 41.7% 56.9% 1.4% 0.0%64 42.2% 46.9% 10.9% 0.0%74 16.2% 83.8% 0.0% 0.0%83 30.1% 62.7% 6.0% 1.2%44 2.3% 93.2% 4.5% 0.0%51 7.8% 84.3% 7.8% 0.0%50 6.0% 80.0% 14.0% 0.0%43 27.9% 65.1% 7.0% 0.0%39 17.9% 76.9% 5.1% 0.0%181 5.5% 87.3% 7.2% 0.0%157 10.2% 84.1% 5.7% 0.0%161 11.8% 83.9% 4.3% 0.0%167 7.2% 87.4% 5.4% 0.0%17 17.6% 82.4% 0.0% 0.0%9 0.0% 100.0% 0.0% 0.0%9 0.0% 88.9% 11.1% 0.0%61 4.9% 82.0% 6.6% 6.6%8 12.5% 87.5% 0.0% 0.0%44 22.7% 63.6% 13.6% 0.0%71 33.8% 45.1% 19.7% 1.4%17 5.9% 94.1% 0.0% 0.0%197 10.2% 69.5% 15.7% 4.6%156 7.7% 83.3% 9.0% 0.0%192 13.5% 73.4% 13.0% 0.0%145 9.0% 74.5% 14.5% 2.1%8 50.0% 50.0% 0.0% 0.0%4 50.0% 25.0% 25.0% 0.0%23 4.3% 91.3% 4.3% 0.0%24 8.3% 91.7% 0.0% 0.0%61 24.6% 63.9% 11.5% 0.0%74 18.9% 68.9% 10.8% 1.4%17 17.6% 76.5% 5.9% 0.0%16 31.3% 68.8% 0.0% 0.0%15 26.7% 73.3% 0.0% 0.0%169 17.2% 73.4% 9.5% 0.0%19 21.1% 73.7% 5.3% 0.0%17 17.6% 64.7% 17.6% 0.0%11 9.1% 81.8% 9.1% 0.0%42 14.3% 81.0% 4.8% 0.0%4 75.0% 0.0% 25.0% 0.0%6 100.0% 0.0% 0.0% 0.0%18 5.6% 94.4% 0.0% 0.0%27 25.9% 70.4% 3.7% 0.0%22 9.1% 81.8% 9.1% 0.0%17 17.6% 64.7% 17.6% 0.0%14 0.0% 100.0% 0.0% 0.0%123 13.8% 83.7% 2.4% 0.0%124 11.3% 83.9% 4.8% 0.0%126 21.4% 73.8% 4.8% 0.0%142 9.2% 83.1% 7.7% 0.0%64 3.1% 90.6% 6.3% 0.0%47 8.5% 89.4% 2.1% 0.0%9 0.0% 88.9% 11.1% 0.0%91 5.5% 91.2% 3.3% 0.0%137 5.1% 90.5% 4.4% 0.0%61 16.4% 82.0% 1.6% 0.0%30 10.0% 90.0% 0.0% 0.0%190 15.8% 66.8% 17.4% 0.0%121 16.5% 67.8% 15.7% 0.0%119 8.4% 89.9% 0.8% 0.8%47 8.5% 87.2% 4.3% 0.0%74 2.7% 90.5% 5.4% 1.4%21 9.5% 90.5% 0.0% 0.0%30 13.3% 83.3% 0.0% 3.3%28 17.9% 82.1% 0.0% 0.0%47 4.3% 87.2% 8.5% 0.0%64 35.9% 59.4% 4.7% 0.0%113 7.1% 88.5% 4.4% 0.0%16 12.5% 87.5% 0.0% 0.0%12 33.3% 50.0% 16.7% 0.0%35 5.7% 80.0% 14.3% 0.0%33 12.1% 84.8% 3.0% 0.0%23 4.3% 82.6% 13.0% 0.0%25 0.0% 84.0% 16.0% 0.0%7 14.3% 85.7% 0.0% 0.0%27 11.1% 88.9% 0.0% 0.0%40 7.5% 92.5% 0.0% 0.0%41 9.8% 90.2% 0.0% 0.0%41 12.2% 87.8% 0.0% 0.0%16 0.0% 100.0% 0.0% 0.0%17 0.0% 100.0% 0.0% 0.0%17 5.9% 88.2% 5.9% 0.0%38 15.8% 76.3% 7.9% 0.0%31 29.0% 58.1% 12.9% 0.0%198 6.1% 88.9% 5.1% 0.0%71 14.1% 84.5% 1.4% 0.0%26 23.1% 76.9% 0.0% 0.0%32 21.9% 78.1% 0.0% 0.0%11 0.0% 100.0% 0.0% 0.0%27 0.0% 85.2% 7.4% 7.4%41 9.8% 82.9% 7.3% 0.0%37 24.3% 70.3% 5.4% 0.0%12 8.3% 75.0% 16.7% 0.0%12 16.7% 66.7% 16.7% 0.0%9 0.0% 100.0% 0.0% 0.0%103 13.6% 78.6% 6.8% 1.0%114 24.6% 67.5% 7.9% 0.0%95 7.4% 87.4% 5.3% 0.0%15 6.7% 93.3% 0.0% 0.0%14 0.0% 100.0% 0.0% 0.0%50 2.0% 94.0% 4.0% 0.0%49 42.9% 49.0% 8.2% 0.0%22 50.0% 40.9% 9.1% 0.0%18 27.8% 66.7% 5.6% 0.0%19 42.1% 57.9% 0.0% 0.0%37 2.7% 94.6% 2.7% 0.0%31 0.0% 96.8% 3.2% 0.0%36 5.6% 94.4% 0.0% 0.0%112 8.9% 86.6% 4.5% 0.0%17 23.5% 70.6% 5.9% 0.0%30 16.7% 83.3% 0.0% 0.0%18956 13.5% 78.9% 6.9% 0.7%

18


3hd Festival

4GB



Awakenings Festival



BPM Festival



CommunikeyComunite


Crssd Festival

CTM




Dirty Bird Campout

donaufestival



Electron Festival




FutureEverything


Heart of Noise





intonal


Krake Festival

L.E.V. Festival


LEM Festival

Lente Kabinet





LoveboxLunchmeat


Mamby on the Beach


MEM



Movement Detroit


Mutek Barcelona

Mutek Montreal

Mutek MX



Nördik Impakt

Novas Frequencias

Nuits Sonores



Rainbow Disco Club

Rewire

Rokolectiv

RoskildeSchiev






springfestival


STRP BIËNNALE



Time Warp Argentina


Together Festival


Unsound Adelaide

Unsound Krakow


Volt Festival



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19 47.4% 47.4% 5.3% 0.0% 23 47.8% 43.5% 8.7% 0.0% 32 3.1% 96.9% 0.0% 0.0% 46 0.0% 100.0% 0.0% 0.0% 9 44.4% 55.6% 0.0% 0.0% 25 0.0% 100.0% 0.0% 0.0% 41 7.3% 92.7% 0.0% 0.0% 32 3.1% 96.9% 0.0% 0.0% 31 3.2% 93.5% 3.2% 0.0% 56 8.9% 89.3% 1.8% 0.0%130 24.6% 73.1% 2.3% 0.0% 27 7.4% 85.2% 7.4% 0.0% 44 15.9% 72.7% 4.5% 6.8%110 10.0% 86.4% 3.6% 0.0%103 6.8% 90.3% 2.9% 0.0%112 15.2% 83.0% 1.8% 0.0% 17 17.6% 82.4% 0.0% 0.0% 70 4.3% 90.0% 5.7% 0.0% 89 16.9% 75.3% 7.9% 0.0% 67 3.0% 92.5% 4.5% 0.0% 87 13.8% 75.9% 10.3% 0.0%229 16.2% 72.1% 11.8% 0.0%171 2.9% 90.6% 2.3% 4.1% 24 4.2% 83.3% 12.5% 0.0% 26 15.4% 80.8% 3.8% 0.0%152 5.3% 94.1% 0.7% 0.0%377 9.3% 88.9% 1.1% 0.8%134 21.6% 68.7% 9.7% 0.0% 82 17.1% 65.9% 17.1% 0.0% 21 14.3% 76.2% 9.5% 0.0% 30 3.3% 80.0% 16.7% 0.0% 36 16.7% 77.8% 5.6% 0.0% 6 16.7% 66.7% 16.7% 0.0% 52 17.3% 76.9% 3.8% 1.9% 34 17.6% 70.6% 5.9% 5.9% 33 12.1% 57.6% 30.3% 0.0% 17 29.4% 52.9% 17.6% 0.0% 22 13.6% 81.8% 4.5% 0.0% 34 17.6% 82.4% 0.0% 0.0% 40 12.5% 85.0% 2.5% 0.0% 12 8.3% 91.7% 0.0% 0.0% 12 8.3% 91.7% 0.0% 0.0% 41 7.3% 92.7% 0.0% 0.0% 45 8.9% 86.7% 4.4% 0.0%146 22.6% 73.3% 4.1% 0.0%187 32.1% 58.3% 9.6% 0.0%198 42.9% 53.5% 2.5% 1.0%101 14.9% 76.2% 8.9% 0.0%181 9.9% 84.5% 3.9% 1.7%13 30.8% 53.8% 15.4% 0.0%69 13.0% 75.4% 11.6% 0.0%131 15.3% 84.0% 0.8% 0.0%145 12.4% 82.1% 5.5% 0.0%103 4.9% 95.1% 0.0% 0.0%23 13.0% 87.0% 0.0% 0.0%80 2.5% 96.3% 1.3% 0.0%54 20.4% 79.6% 0.0% 0.0%33 3.0% 97.0% 0.0% 0.0%16 18.8% 81.3% 0.0% 0.0%10 0.0% 100.0% 0.0% 0.0%71 7.0% 93.0% 0.0% 0.0%37 5.4% 91.9% 0.0% 2.7%41 4.9% 92.7% 2.4% 0.0%35 5.7% 88.6% 5.7% 0.0%35 2.9% 94.3% 2.9% 0.0%39 12.8% 69.2% 17.9% 0.0%49 8.2% 71.4% 18.4% 2.0%232 2.2% 90.5% 7.3% 0.0%18 50.0% 5.6% 44.4% 0.0%29 3.4% 86.2% 10.3% 0.0%81 7.4% 87.7% 4.9% 0.0%57 1.8% 94.7% 3.5% 0.0%33 30.3% 54.5% 15.2% 0.0%13 53.8% 46.2% 0.0% 0.0%16 25.0% 62.5% 0.0% 12.5%20 10.0% 50.0% 40.0% 0.0%14 21.4% 64.3% 14.3% 0.0%15 6.7% 93.3% 0.0% 0.0%95 21.1% 74.7% 4.2% 0.0%71 5.6% 87.3% 4.2% 2.8%99 12.1% 82.8% 5.1% 0.0%97 6.2% 87.6% 6.2% 0.0%13 7.7% 84.6% 7.7% 0.0%12 0.0% 100.0% 0.0% 0.0%10 30.0% 70.0% 0.0% 0.0%16 25.0% 68.8% 6.3% 0.0%44 13.6% 84.1% 2.3% 0.0%14 14.3% 71.4% 14.3% 0.0%41 7.3% 90.2% 2.4% 0.0%133 5.3% 76.7% 18.0% 0.0%26 26.9% 57.7% 15.4% 0.0%32 21.9% 71.9% 6.3% 0.0%37 29.7% 62.2% 8.1% 0.0%9 11.1% 88.9% 0.0% 0.0% 88 13.6% 75.0% 1.1% 10.2%61 6.6% 83.6% 9.8% 0.0%552 10.9% 71.0% 14.9% 3.3%726 10.9% 72.7% 14.0% 2.3%251 9.6% 69.3% 21.1% 0.0%27 11.1% 81.5% 3.7% 3.7%21 19.0% 66.7% 14.3% 0.0%22 4.5% 90.9% 4.5% 0.0%52 15.4% 78.8% 5.8% 0.0%30 6.7% 80.0% 13.3% 0.0%10 20.0% 80.0% 0.0% 0.0%10 0.0% 90.0% 10.0% 0.0%10 0.0% 100.0% 0.0% 0.0%14 0.0% 100.0% 0.0% 0.0%28 7.1% 89.3% 3.6% 0.0%26 7.7% 84.6% 7.7% 0.0%25 24.0% 76.0% 0.0% 0.0%142 9.2% 89.4% 1.4% 0.0%78 47.4% 44.9% 7.7% 0.0%28 7.1% 92.9% 0.0% 0.0%37 0.0% 97.3% 2.7% 0.0%36 5.6% 91.7% 2.8% 0.0%21 0.0% 100.0% 0.0% 0.0%24 0.0% 100.0% 0.0% 0.0%35 17.1% 74.3% 8.6% 0.0%118 16.9% 79.7% 1.7% 1.7%109 35.8% 60.6% 3.7% 0.0%71 23.9% 70.4% 5.6% 0.0%73 8.2% 91.8% 0.0% 0.0%34 26.5% 67.6% 5.9% 0.0%26 30.8% 61.5% 7.7% 0.0%22 18.2% 59.1% 22.7% 0.0%26 26.9% 61.5% 11.5% 0.0%38 31.6% 55.3% 10.5% 2.6%41 51.2% 41.5% 7.3% 0.0%9 0.0% 66.7% 33.3% 0.0%17 5.9% 88.2% 5.9% 0.0%13 15.4% 61.5% 23.1% 0.0%22 4.5% 81.8% 13.6% 0.0%48 18.8% 70.8% 10.4% 0.0%49 16.3% 81.6% 2.0% 0.0%42 14.3% 83.3% 2.4% 0.0%37 10.8% 89.2% 0.0% 0.0%20 5.0% 95.0% 0.0% 0.0%30 13.3% 86.7% 0.0% 0.0%21 4.8% 85.7% 9.5% 0.0%12 8.3% 75.0% 16.7% 0.0%16 0.0% 100.0% 0.0% 0.0%17 17.6% 82.4% 0.0% 0.0%11 18.2% 81.8% 0.0% 0.0%15 6.7% 93.3% 0.0% 0.0%22 9.1% 68.2% 22.7% 0.0%29 6.9% 79.3% 13.8% 0.0%29 3.4% 93.1% 3.4% 0.0%26 19.2% 76.9% 3.8% 0.0%26 84.6% 0.0% 15.4% 0.0%10 10.0% 90.0% 0.0% 0.0%8 0.0% 75.0% 25.0% 0.0%12 25.0% 66.7% 8.3% 0.0%13 7.7% 84.6% 7.7% 0.0%12 16.7% 66.7% 16.7% 0.0%72 11.1% 80.6% 8.3% 0.0%105 13.3% 72.4% 14.3% 0.0%126 1.6% 98.4% 0.0% 0.0%124 4.0% 83.9% 10.5% 1.6%101 13.9% 80.2% 5.9% 0.0%166 11.4% 75.9% 7.2% 5.4%36 27.8% 72.2% 0.0% 0.0%38 26.3% 68.4% 5.3% 0.0%22 13.6% 68.2% 18.2% 0.0%38 7.9% 78.9% 10.5% 2.6%64 6.3% 92.2% 1.6% 0.0%10 0.0% 100.0% 0.0% 0.0%29 31.0% 69.0% 0.0% 0.0%37 29.7% 64.9% 5.4% 0.0%42 14.3% 81.0% 4.8% 0.0%61 16.4% 78.7% 4.9% 0.0%32 9.4% 81.3% 9.4% 0.0%66 91.0% 84.8% 9.1% 0.0%120 10.8% 80.8% 8.3% 0.0%121 14.9% 80.2% 5.0% 0.0%59 8.5% 81.4% 10.2% 0.0%72 9.7% 80.6% 9.7% 0.0%23 26.1% 43.5% 30.4% 0.0%17 41.2% 52.9% 5.9% 0.0%20 5.0% 90.0% 5.0% 0.0%32 12.5% 78.1% 9.4% 0.0%50 6.0% 88.0% 6.0% 0.0%21 4.8% 95.2% 0.0% 0.0%41 7.3% 92.7% 0.0% 0.0%114 25.4% 70.2% 4.4% 0.0%88 34.1% 56.8% 9.1% 0.0%143 7.0% 90.9% 0.7% 1.4%124 12.9% 83.9% 1.6% 1.6%113 9.7% 85.8% 4.4% 0.0%77 10.4% 88.3% 1.3% 0.0%28 21.4% 64.3% 14.3% 0.0%10 10.0% 20.0% 70.0% 0.0%69 23.2% 72.5% 4.3% 0.0%51 23.5% 68.6% 7.8% 0.0%17 11.8% 76.5% 11.8% 0.0%31 12.9% 87.1% 0.0% 0.0%25 28.0% 64.0% 8.0% 0.0%27 7.4% 88.9% 3.7% 0.0%24 4.2% 91.7% 4.2% 0.0%77 10.4% 80.5% 1.3% 7.8%81 18.5% 72.8% 8.6% 0.0%56 7.1% 82.1% 10.7% 0.0%104 7.7% 86.5% 5.8% 0.0%49 8.2% 89.8% 2.0% 0.0%64 12.5% 81.3% 6.3% 0.0%109 10.1% 85.3% 1.8% 2.8%36 11.1% 83.3% 5.6% 0.0%48 6.3% 93.8% 0.0% 0.0%38 28.9% 65.8% 5.3% 0.0%54 13.0% 79.6% 1.9% 5.6%17 11.8% 88.2% 0.0% 0.0% 72 41.7% 56.9% 1.4% 0.0%64 42.2% 46.9% 10.9% 0.0%74 16.2% 83.8% 0.0% 0.0%83 30.1% 62.7% 6.0% 1.2%44 2.3% 93.2% 4.5% 0.0%51 7.8% 84.3% 7.8% 0.0%50 6.0% 80.0% 14.0% 0.0%43 27.9% 65.1% 7.0% 0.0%39 17.9% 76.9% 5.1% 0.0%181 5.5% 87.3% 7.2% 0.0%157 10.2% 84.1% 5.7% 0.0%161 11.8% 83.9% 4.3% 0.0%167 7.2% 87.4% 5.4% 0.0%17 17.6% 82.4% 0.0% 0.0%9 0.0% 100.0% 0.0% 0.0%9 0.0% 88.9% 11.1% 0.0%61 4.9% 82.0% 6.6% 6.6%8 12.5% 87.5% 0.0% 0.0%44 22.7% 63.6% 13.6% 0.0%71 33.8% 45.1% 19.7% 1.4%17 5.9% 94.1% 0.0% 0.0%197 10.2% 69.5% 15.7% 4.6%156 7.7% 83.3% 9.0% 0.0%192 13.5% 73.4% 13.0% 0.0%145 9.0% 74.5% 14.5% 2.1%8 50.0% 50.0% 0.0% 0.0%4 50.0% 25.0% 25.0% 0.0%23 4.3% 91.3% 4.3% 0.0%24 8.3% 91.7% 0.0% 0.0%61 24.6% 63.9% 11.5% 0.0%74 18.9% 68.9% 10.8% 1.4%17 17.6% 76.5% 5.9% 0.0%16 31.3% 68.8% 0.0% 0.0%15 26.7% 73.3% 0.0% 0.0%169 17.2% 73.4% 9.5% 0.0%19 21.1% 73.7% 5.3% 0.0%17 17.6% 64.7% 17.6% 0.0%11 9.1% 81.8% 9.1% 0.0%42 14.3% 81.0% 4.8% 0.0%4 75.0% 0.0% 25.0% 0.0%6 100.0% 0.0% 0.0% 0.0%18 5.6% 94.4% 0.0% 0.0%27 25.9% 70.4% 3.7% 0.0%22 9.1% 81.8% 9.1% 0.0%17 17.6% 64.7% 17.6% 0.0%14 0.0% 100.0% 0.0% 0.0%123 13.8% 83.7% 2.4% 0.0%124 11.3% 83.9% 4.8% 0.0%126 21.4% 73.8% 4.8% 0.0%142 9.2% 83.1% 7.7% 0.0%64 3.1% 90.6% 6.3% 0.0%47 8.5% 89.4% 2.1% 0.0%9 0.0% 88.9% 11.1% 0.0%91 5.5% 91.2% 3.3% 0.0%137 5.1% 90.5% 4.4% 0.0%61 16.4% 82.0% 1.6% 0.0%30 10.0% 90.0% 0.0% 0.0%190 15.8% 66.8% 17.4% 0.0%121 16.5% 67.8% 15.7% 0.0%119 8.4% 89.9% 0.8% 0.8%47 8.5% 87.2% 4.3% 0.0%74 2.7% 90.5% 5.4% 1.4%21 9.5% 90.5% 0.0% 0.0%30 13.3% 83.3% 0.0% 3.3%28 17.9% 82.1% 0.0% 0.0%47 4.3% 87.2% 8.5% 0.0%64 35.9% 59.4% 4.7% 0.0%113 7.1% 88.5% 4.4% 0.0%16 12.5% 87.5% 0.0% 0.0%12 33.3% 50.0% 16.7% 0.0%35 5.7% 80.0% 14.3% 0.0%33 12.1% 84.8% 3.0% 0.0%23 4.3% 82.6% 13.0% 0.0%25 0.0% 84.0% 16.0% 0.0%7 14.3% 85.7% 0.0% 0.0%27 11.1% 88.9% 0.0% 0.0%40 7.5% 92.5% 0.0% 0.0%41 9.8% 90.2% 0.0% 0.0%41 12.2% 87.8% 0.0% 0.0%16 0.0% 100.0% 0.0% 0.0%17 0.0% 100.0% 0.0% 0.0%17 5.9% 88.2% 5.9% 0.0%38 15.8% 76.3% 7.9% 0.0%31 29.0% 58.1% 12.9% 0.0%198 6.1% 88.9% 5.1% 0.0%71 14.1% 84.5% 1.4% 0.0%26 23.1% 76.9% 0.0% 0.0%32 21.9% 78.1% 0.0% 0.0%11 0.0% 100.0% 0.0% 0.0%27 0.0% 85.2% 7.4% 7.4%41 9.8% 82.9% 7.3% 0.0%37 24.3% 70.3% 5.4% 0.0%12 8.3% 75.0% 16.7% 0.0%12 16.7% 66.7% 16.7% 0.0%9 0.0% 100.0% 0.0% 0.0%103 13.6% 78.6% 6.8% 1.0%114 24.6% 67.5% 7.9% 0.0%95 7.4% 87.4% 5.3% 0.0%15 6.7% 93.3% 0.0% 0.0%14 0.0% 100.0% 0.0% 0.0%50 2.0% 94.0% 4.0% 0.0%49 42.9% 49.0% 8.2% 0.0%22 50.0% 40.9% 9.1% 0.0%18 27.8% 66.7% 5.6% 0.0%19 42.1% 57.9% 0.0% 0.0%37 2.7% 94.6% 2.7% 0.0%31 0.0% 96.8% 3.2% 0.0%36 5.6% 94.4% 0.0% 0.0%112 8.9% 86.6% 4.5% 0.0%17 23.5% 70.6% 5.9% 0.0%30 16.7% 83.3% 0.0% 0.0%18956 13.5% 78.9% 6.9% 0.7%

18 19



3hd Festival

4GB



Awakenings Festival



BPM Festival



CommunikeyComunite


Crssd Festival

CTM




Dirty Bird Campout

donaufestival



Electron Festival




FutureEverything


Heart of Noise





intonal


Krake Festival

L.E.V. Festival


LEM Festival

Lente Kabinet





LoveboxLunchmeat


Mamby on the Beach


MEM



Movement Detroit


Mutek Barcelona

Mutek Montreal

Mutek MX



Nördik Impakt

Novas Frequencias

Nuits Sonores



Rainbow Disco Club

Rewire

Rokolectiv

RoskildeSchiev






springfestival


STRP BIËNNALE



Time Warp Argentina


Together Festival


Unsound Adelaide

Unsound Krakow


Volt Festival



2015201620162017201220162016201620172014201220162017201520162017201620152016201420122014201220152016201520162013201220152016201720142016201520162017201320162017201620172016201720152016201720142013201620162015201420152016201420172016201620162016201620172015201620152016201220122012201220122016201720152016201720132016201720142013201520162017201420162014201620122015201620172013201420162015201620122015201620132016201720172017201620172015201620172017201720142012201420162014201520152016201720152015201620142015201620172014201420152016201520162014201320152016201420142015201620172014201520162016201720132015201620152016201420162017201320162017201620152016201220142014201420152016201620172016201620152016201220142015201620122016201420162014201620172015201620172013201220162015201620152016201720142013201520162012201420152016201620142012201620142014201520162012201420152016201420152016201520162017201320142016201620162016201620162015201520162017201420152016201620172016201720152016201720152015201620162016201520162016201520162016201620152016201720142013201220162015201620132012201520122016201720132014201620172015201720122016201720152016201720122016201620152016201720152016201520152016201220152016201720142014201520162015201620122015201620122012201420132015201620122013201620122014201720162014

19 47.4% 47.4% 5.3% 0.0% 23 47.8% 43.5% 8.7% 0.0% 32 3.1% 96.9% 0.0% 0.0% 46 0.0% 100.0% 0.0% 0.0% 9 44.4% 55.6% 0.0% 0.0% 25 0.0% 100.0% 0.0% 0.0% 41 7.3% 92.7% 0.0% 0.0% 32 3.1% 96.9% 0.0% 0.0% 31 3.2% 93.5% 3.2% 0.0% 56 8.9% 89.3% 1.8% 0.0%130 24.6% 73.1% 2.3% 0.0% 27 7.4% 85.2% 7.4% 0.0% 44 15.9% 72.7% 4.5% 6.8%110 10.0% 86.4% 3.6% 0.0%103 6.8% 90.3% 2.9% 0.0%112 15.2% 83.0% 1.8% 0.0% 17 17.6% 82.4% 0.0% 0.0% 70 4.3% 90.0% 5.7% 0.0% 89 16.9% 75.3% 7.9% 0.0% 67 3.0% 92.5% 4.5% 0.0% 87 13.8% 75.9% 10.3% 0.0%229 16.2% 72.1% 11.8% 0.0%171 2.9% 90.6% 2.3% 4.1% 24 4.2% 83.3% 12.5% 0.0% 26 15.4% 80.8% 3.8% 0.0%152 5.3% 94.1% 0.7% 0.0%377 9.3% 88.9% 1.1% 0.8%134 21.6% 68.7% 9.7% 0.0% 82 17.1% 65.9% 17.1% 0.0% 21 14.3% 76.2% 9.5% 0.0% 30 3.3% 80.0% 16.7% 0.0% 36 16.7% 77.8% 5.6% 0.0% 6 16.7% 66.7% 16.7% 0.0% 52 17.3% 76.9% 3.8% 1.9% 34 17.6% 70.6% 5.9% 5.9% 33 12.1% 57.6% 30.3% 0.0% 17 29.4% 52.9% 17.6% 0.0% 22 13.6% 81.8% 4.5% 0.0% 34 17.6% 82.4% 0.0% 0.0% 40 12.5% 85.0% 2.5% 0.0% 12 8.3% 91.7% 0.0% 0.0% 12 8.3% 91.7% 0.0% 0.0% 41 7.3% 92.7% 0.0% 0.0% 45 8.9% 86.7% 4.4% 0.0%146 22.6% 73.3% 4.1% 0.0%187 32.1% 58.3% 9.6% 0.0%198 42.9% 53.5% 2.5% 1.0%101 14.9% 76.2% 8.9% 0.0%181 9.9% 84.5% 3.9% 1.7%13 30.8% 53.8% 15.4% 0.0%69 13.0% 75.4% 11.6% 0.0%131 15.3% 84.0% 0.8% 0.0%145 12.4% 82.1% 5.5% 0.0%103 4.9% 95.1% 0.0% 0.0%23 13.0% 87.0% 0.0% 0.0%80 2.5% 96.3% 1.3% 0.0%54 20.4% 79.6% 0.0% 0.0%33 3.0% 97.0% 0.0% 0.0%16 18.8% 81.3% 0.0% 0.0%10 0.0% 100.0% 0.0% 0.0%71 7.0% 93.0% 0.0% 0.0%37 5.4% 91.9% 0.0% 2.7%41 4.9% 92.7% 2.4% 0.0%35 5.7% 88.6% 5.7% 0.0%35 2.9% 94.3% 2.9% 0.0%39 12.8% 69.2% 17.9% 0.0%49 8.2% 71.4% 18.4% 2.0%232 2.2% 90.5% 7.3% 0.0%18 50.0% 5.6% 44.4% 0.0%29 3.4% 86.2% 10.3% 0.0%81 7.4% 87.7% 4.9% 0.0%57 1.8% 94.7% 3.5% 0.0%33 30.3% 54.5% 15.2% 0.0%13 53.8% 46.2% 0.0% 0.0%16 25.0% 62.5% 0.0% 12.5%20 10.0% 50.0% 40.0% 0.0%14 21.4% 64.3% 14.3% 0.0%15 6.7% 93.3% 0.0% 0.0%95 21.1% 74.7% 4.2% 0.0%71 5.6% 87.3% 4.2% 2.8%99 12.1% 82.8% 5.1% 0.0%97 6.2% 87.6% 6.2% 0.0%13 7.7% 84.6% 7.7% 0.0%12 0.0% 100.0% 0.0% 0.0%10 30.0% 70.0% 0.0% 0.0%16 25.0% 68.8% 6.3% 0.0%44 13.6% 84.1% 2.3% 0.0%14 14.3% 71.4% 14.3% 0.0%41 7.3% 90.2% 2.4% 0.0%133 5.3% 76.7% 18.0% 0.0%26 26.9% 57.7% 15.4% 0.0%32 21.9% 71.9% 6.3% 0.0%37 29.7% 62.2% 8.1% 0.0%9 11.1% 88.9% 0.0% 0.0% 88 13.6% 75.0% 1.1% 10.2%61 6.6% 83.6% 9.8% 0.0%552 10.9% 71.0% 14.9% 3.3%726 10.9% 72.7% 14.0% 2.3%251 9.6% 69.3% 21.1% 0.0%27 11.1% 81.5% 3.7% 3.7%21 19.0% 66.7% 14.3% 0.0%22 4.5% 90.9% 4.5% 0.0%52 15.4% 78.8% 5.8% 0.0%30 6.7% 80.0% 13.3% 0.0%10 20.0% 80.0% 0.0% 0.0%10 0.0% 90.0% 10.0% 0.0%10 0.0% 100.0% 0.0% 0.0%14 0.0% 100.0% 0.0% 0.0%28 7.1% 89.3% 3.6% 0.0%26 7.7% 84.6% 7.7% 0.0%25 24.0% 76.0% 0.0% 0.0%142 9.2% 89.4% 1.4% 0.0%78 47.4% 44.9% 7.7% 0.0%28 7.1% 92.9% 0.0% 0.0%37 0.0% 97.3% 2.7% 0.0%36 5.6% 91.7% 2.8% 0.0%21 0.0% 100.0% 0.0% 0.0%24 0.0% 100.0% 0.0% 0.0%35 17.1% 74.3% 8.6% 0.0%118 16.9% 79.7% 1.7% 1.7%109 35.8% 60.6% 3.7% 0.0%71 23.9% 70.4% 5.6% 0.0%73 8.2% 91.8% 0.0% 0.0%34 26.5% 67.6% 5.9% 0.0%26 30.8% 61.5% 7.7% 0.0%22 18.2% 59.1% 22.7% 0.0%26 26.9% 61.5% 11.5% 0.0%38 31.6% 55.3% 10.5% 2.6%41 51.2% 41.5% 7.3% 0.0%9 0.0% 66.7% 33.3% 0.0%17 5.9% 88.2% 5.9% 0.0%13 15.4% 61.5% 23.1% 0.0%22 4.5% 81.8% 13.6% 0.0%48 18.8% 70.8% 10.4% 0.0%49 16.3% 81.6% 2.0% 0.0%42 14.3% 83.3% 2.4% 0.0%37 10.8% 89.2% 0.0% 0.0%20 5.0% 95.0% 0.0% 0.0%30 13.3% 86.7% 0.0% 0.0%21 4.8% 85.7% 9.5% 0.0%12 8.3% 75.0% 16.7% 0.0%16 0.0% 100.0% 0.0% 0.0%17 17.6% 82.4% 0.0% 0.0%11 18.2% 81.8% 0.0% 0.0%15 6.7% 93.3% 0.0% 0.0%22 9.1% 68.2% 22.7% 0.0%29 6.9% 79.3% 13.8% 0.0%29 3.4% 93.1% 3.4% 0.0%26 19.2% 76.9% 3.8% 0.0%26 84.6% 0.0% 15.4% 0.0%10 10.0% 90.0% 0.0% 0.0%8 0.0% 75.0% 25.0% 0.0%12 25.0% 66.7% 8.3% 0.0%13 7.7% 84.6% 7.7% 0.0%12 16.7% 66.7% 16.7% 0.0%72 11.1% 80.6% 8.3% 0.0%105 13.3% 72.4% 14.3% 0.0%126 1.6% 98.4% 0.0% 0.0%124 4.0% 83.9% 10.5% 1.6%101 13.9% 80.2% 5.9% 0.0%166 11.4% 75.9% 7.2% 5.4%36 27.8% 72.2% 0.0% 0.0%38 26.3% 68.4% 5.3% 0.0%22 13.6% 68.2% 18.2% 0.0%38 7.9% 78.9% 10.5% 2.6%64 6.3% 92.2% 1.6% 0.0%10 0.0% 100.0% 0.0% 0.0%29 31.0% 69.0% 0.0% 0.0%37 29.7% 64.9% 5.4% 0.0%42 14.3% 81.0% 4.8% 0.0%61 16.4% 78.7% 4.9% 0.0%32 9.4% 81.3% 9.4% 0.0%66 91.0% 84.8% 9.1% 0.0%120 10.8% 80.8% 8.3% 0.0%121 14.9% 80.2% 5.0% 0.0%59 8.5% 81.4% 10.2% 0.0%72 9.7% 80.6% 9.7% 0.0%23 26.1% 43.5% 30.4% 0.0%17 41.2% 52.9% 5.9% 0.0%20 5.0% 90.0% 5.0% 0.0%32 12.5% 78.1% 9.4% 0.0%50 6.0% 88.0% 6.0% 0.0%21 4.8% 95.2% 0.0% 0.0%41 7.3% 92.7% 0.0% 0.0%114 25.4% 70.2% 4.4% 0.0%88 34.1% 56.8% 9.1% 0.0%143 7.0% 90.9% 0.7% 1.4%124 12.9% 83.9% 1.6% 1.6%113 9.7% 85.8% 4.4% 0.0%77 10.4% 88.3% 1.3% 0.0%28 21.4% 64.3% 14.3% 0.0%10 10.0% 20.0% 70.0% 0.0%69 23.2% 72.5% 4.3% 0.0%51 23.5% 68.6% 7.8% 0.0%17 11.8% 76.5% 11.8% 0.0%31 12.9% 87.1% 0.0% 0.0%25 28.0% 64.0% 8.0% 0.0%27 7.4% 88.9% 3.7% 0.0%24 4.2% 91.7% 4.2% 0.0%77 10.4% 80.5% 1.3% 7.8%81 18.5% 72.8% 8.6% 0.0%56 7.1% 82.1% 10.7% 0.0%104 7.7% 86.5% 5.8% 0.0%49 8.2% 89.8% 2.0% 0.0%64 12.5% 81.3% 6.3% 0.0%109 10.1% 85.3% 1.8% 2.8%36 11.1% 83.3% 5.6% 0.0%48 6.3% 93.8% 0.0% 0.0%38 28.9% 65.8% 5.3% 0.0%54 13.0% 79.6% 1.9% 5.6%17 11.8% 88.2% 0.0% 0.0% 72 41.7% 56.9% 1.4% 0.0%64 42.2% 46.9% 10.9% 0.0%74 16.2% 83.8% 0.0% 0.0%83 30.1% 62.7% 6.0% 1.2%44 2.3% 93.2% 4.5% 0.0%51 7.8% 84.3% 7.8% 0.0%50 6.0% 80.0% 14.0% 0.0%43 27.9% 65.1% 7.0% 0.0%39 17.9% 76.9% 5.1% 0.0%181 5.5% 87.3% 7.2% 0.0%157 10.2% 84.1% 5.7% 0.0%161 11.8% 83.9% 4.3% 0.0%167 7.2% 87.4% 5.4% 0.0%17 17.6% 82.4% 0.0% 0.0%9 0.0% 100.0% 0.0% 0.0%9 0.0% 88.9% 11.1% 0.0%61 4.9% 82.0% 6.6% 6.6%8 12.5% 87.5% 0.0% 0.0%44 22.7% 63.6% 13.6% 0.0%71 33.8% 45.1% 19.7% 1.4%17 5.9% 94.1% 0.0% 0.0%197 10.2% 69.5% 15.7% 4.6%156 7.7% 83.3% 9.0% 0.0%192 13.5% 73.4% 13.0% 0.0%145 9.0% 74.5% 14.5% 2.1%8 50.0% 50.0% 0.0% 0.0%4 50.0% 25.0% 25.0% 0.0%23 4.3% 91.3% 4.3% 0.0%24 8.3% 91.7% 0.0% 0.0%61 24.6% 63.9% 11.5% 0.0%74 18.9% 68.9% 10.8% 1.4%17 17.6% 76.5% 5.9% 0.0%16 31.3% 68.8% 0.0% 0.0%15 26.7% 73.3% 0.0% 0.0%169 17.2% 73.4% 9.5% 0.0%19 21.1% 73.7% 5.3% 0.0%17 17.6% 64.7% 17.6% 0.0%11 9.1% 81.8% 9.1% 0.0%42 14.3% 81.0% 4.8% 0.0%4 75.0% 0.0% 25.0% 0.0%6 100.0% 0.0% 0.0% 0.0%18 5.6% 94.4% 0.0% 0.0%27 25.9% 70.4% 3.7% 0.0%22 9.1% 81.8% 9.1% 0.0%17 17.6% 64.7% 17.6% 0.0%14 0.0% 100.0% 0.0% 0.0%123 13.8% 83.7% 2.4% 0.0%124 11.3% 83.9% 4.8% 0.0%126 21.4% 73.8% 4.8% 0.0%142 9.2% 83.1% 7.7% 0.0%64 3.1% 90.6% 6.3% 0.0%47 8.5% 89.4% 2.1% 0.0%9 0.0% 88.9% 11.1% 0.0%91 5.5% 91.2% 3.3% 0.0%137 5.1% 90.5% 4.4% 0.0%61 16.4% 82.0% 1.6% 0.0%30 10.0% 90.0% 0.0% 0.0%190 15.8% 66.8% 17.4% 0.0%121 16.5% 67.8% 15.7% 0.0%119 8.4% 89.9% 0.8% 0.8%47 8.5% 87.2% 4.3% 0.0%74 2.7% 90.5% 5.4% 1.4%21 9.5% 90.5% 0.0% 0.0%30 13.3% 83.3% 0.0% 3.3%28 17.9% 82.1% 0.0% 0.0%47 4.3% 87.2% 8.5% 0.0%64 35.9% 59.4% 4.7% 0.0%113 7.1% 88.5% 4.4% 0.0%16 12.5% 87.5% 0.0% 0.0%12 33.3% 50.0% 16.7% 0.0%35 5.7% 80.0% 14.3% 0.0%33 12.1% 84.8% 3.0% 0.0%23 4.3% 82.6% 13.0% 0.0%25 0.0% 84.0% 16.0% 0.0%7 14.3% 85.7% 0.0% 0.0%27 11.1% 88.9% 0.0% 0.0%40 7.5% 92.5% 0.0% 0.0%41 9.8% 90.2% 0.0% 0.0%41 12.2% 87.8% 0.0% 0.0%16 0.0% 100.0% 0.0% 0.0%17 0.0% 100.0% 0.0% 0.0%17 5.9% 88.2% 5.9% 0.0%38 15.8% 76.3% 7.9% 0.0%31 29.0% 58.1% 12.9% 0.0%198 6.1% 88.9% 5.1% 0.0%71 14.1% 84.5% 1.4% 0.0%26 23.1% 76.9% 0.0% 0.0%32 21.9% 78.1% 0.0% 0.0%11 0.0% 100.0% 0.0% 0.0%27 0.0% 85.2% 7.4% 7.4%41 9.8% 82.9% 7.3% 0.0%37 24.3% 70.3% 5.4% 0.0%12 8.3% 75.0% 16.7% 0.0%12 16.7% 66.7% 16.7% 0.0%9 0.0% 100.0% 0.0% 0.0%103 13.6% 78.6% 6.8% 1.0%114 24.6% 67.5% 7.9% 0.0%95 7.4% 87.4% 5.3% 0.0%15 6.7% 93.3% 0.0% 0.0%14 0.0% 100.0% 0.0% 0.0%50 2.0% 94.0% 4.0% 0.0%49 42.9% 49.0% 8.2% 0.0%22 50.0% 40.9% 9.1% 0.0%18 27.8% 66.7% 5.6% 0.0%19 42.1% 57.9% 0.0% 0.0%37 2.7% 94.6% 2.7% 0.0%31 0.0% 96.8% 3.2% 0.0%36 5.6% 94.4% 0.0% 0.0%112 8.9% 86.6% 4.5% 0.0%17 23.5% 70.6% 5.9% 0.0%30 16.7% 83.3% 0.0% 0.0%18956 13.5% 78.9% 6.9% 0.7%

20

3hd Festival

4GB



Awakenings Festival



BPM Festival



CommunikeyComunite


Crssd Festival

CTM




Dirty Bird Campout

donaufestival



Electron Festival




FutureEverything


Heart of Noise





intonal


Krake Festival

L.E.V. Festival


LEM Festival

Lente Kabinet





LoveboxLunchmeat


Mamby on the Beach


MEM



Movement Detroit


Mutek Barcelona

Mutek Montreal

Mutek MX



Nördik Impakt

Novas Frequencias

Nuits Sonores



Rainbow Disco Club

Rewire

Rokolectiv

RoskildeSchiev






springfestival


STRP BIËNNALE



Time Warp Argentina


Together Festival


Unsound Adelaide

Unsound Krakow


Volt Festival



2015201620162017201220162016201620172014201220162017201520162017201620152016201420122014201220152016201520162013201220152016201720142016201520162017201320162017201620172016201720152016201720142013201620162015201420152016201420172016201620162016201620172015201620152016201220122012201220122016201720152016201720132016201720142013201520162017201420162014201620122015201620172013201420162015201620122015201620132016201720172017201620172015201620172017201720142012201420162014201520152016201720152015201620142015201620172014201420152016201520162014201320152016201420142015201620172014201520162016201720132015201620152016201420162017201320162017201620152016201220142014201420152016201620172016201620152016201220142015201620122016201420162014201620172015201620172013201220162015201620152016201720142013201520162012201420152016201620142012201620142014201520162012201420152016201420152016201520162017201320142016201620162016201620162015201520162017201420152016201620172016201720152016201720152015201620162016201520162016201520162016201620152016201720142013201220162015201620132012201520122016201720132014201620172015201720122016201720152016201720122016201620152016201720152016201520152016201220152016201720142014201520162015201620122015201620122012201420132015201620122013201620122014201720162014

19 47.4% 47.4% 5.3% 0.0% 23 47.8% 43.5% 8.7% 0.0% 32 3.1% 96.9% 0.0% 0.0% 46 0.0% 100.0% 0.0% 0.0% 9 44.4% 55.6% 0.0% 0.0% 25 0.0% 100.0% 0.0% 0.0% 41 7.3% 92.7% 0.0% 0.0% 32 3.1% 96.9% 0.0% 0.0% 31 3.2% 93.5% 3.2% 0.0% 56 8.9% 89.3% 1.8% 0.0%130 24.6% 73.1% 2.3% 0.0% 27 7.4% 85.2% 7.4% 0.0% 44 15.9% 72.7% 4.5% 6.8%110 10.0% 86.4% 3.6% 0.0%103 6.8% 90.3% 2.9% 0.0%112 15.2% 83.0% 1.8% 0.0% 17 17.6% 82.4% 0.0% 0.0% 70 4.3% 90.0% 5.7% 0.0% 89 16.9% 75.3% 7.9% 0.0% 67 3.0% 92.5% 4.5% 0.0% 87 13.8% 75.9% 10.3% 0.0%229 16.2% 72.1% 11.8% 0.0%171 2.9% 90.6% 2.3% 4.1% 24 4.2% 83.3% 12.5% 0.0% 26 15.4% 80.8% 3.8% 0.0%152 5.3% 94.1% 0.7% 0.0%377 9.3% 88.9% 1.1% 0.8%134 21.6% 68.7% 9.7% 0.0% 82 17.1% 65.9% 17.1% 0.0% 21 14.3% 76.2% 9.5% 0.0% 30 3.3% 80.0% 16.7% 0.0% 36 16.7% 77.8% 5.6% 0.0% 6 16.7% 66.7% 16.7% 0.0% 52 17.3% 76.9% 3.8% 1.9% 34 17.6% 70.6% 5.9% 5.9% 33 12.1% 57.6% 30.3% 0.0% 17 29.4% 52.9% 17.6% 0.0% 22 13.6% 81.8% 4.5% 0.0% 34 17.6% 82.4% 0.0% 0.0% 40 12.5% 85.0% 2.5% 0.0% 12 8.3% 91.7% 0.0% 0.0% 12 8.3% 91.7% 0.0% 0.0% 41 7.3% 92.7% 0.0% 0.0% 45 8.9% 86.7% 4.4% 0.0%146 22.6% 73.3% 4.1% 0.0%187 32.1% 58.3% 9.6% 0.0%198 42.9% 53.5% 2.5% 1.0%101 14.9% 76.2% 8.9% 0.0%181 9.9% 84.5% 3.9% 1.7%13 30.8% 53.8% 15.4% 0.0%69 13.0% 75.4% 11.6% 0.0%131 15.3% 84.0% 0.8% 0.0%145 12.4% 82.1% 5.5% 0.0%103 4.9% 95.1% 0.0% 0.0%23 13.0% 87.0% 0.0% 0.0%80 2.5% 96.3% 1.3% 0.0%54 20.4% 79.6% 0.0% 0.0%33 3.0% 97.0% 0.0% 0.0%16 18.8% 81.3% 0.0% 0.0%10 0.0% 100.0% 0.0% 0.0%71 7.0% 93.0% 0.0% 0.0%37 5.4% 91.9% 0.0% 2.7%41 4.9% 92.7% 2.4% 0.0%35 5.7% 88.6% 5.7% 0.0%35 2.9% 94.3% 2.9% 0.0%39 12.8% 69.2% 17.9% 0.0%49 8.2% 71.4% 18.4% 2.0%232 2.2% 90.5% 7.3% 0.0%18 50.0% 5.6% 44.4% 0.0%29 3.4% 86.2% 10.3% 0.0%81 7.4% 87.7% 4.9% 0.0%57 1.8% 94.7% 3.5% 0.0%33 30.3% 54.5% 15.2% 0.0%13 53.8% 46.2% 0.0% 0.0%16 25.0% 62.5% 0.0% 12.5%20 10.0% 50.0% 40.0% 0.0%14 21.4% 64.3% 14.3% 0.0%15 6.7% 93.3% 0.0% 0.0%95 21.1% 74.7% 4.2% 0.0%71 5.6% 87.3% 4.2% 2.8%99 12.1% 82.8% 5.1% 0.0%97 6.2% 87.6% 6.2% 0.0%13 7.7% 84.6% 7.7% 0.0%12 0.0% 100.0% 0.0% 0.0%10 30.0% 70.0% 0.0% 0.0%16 25.0% 68.8% 6.3% 0.0%44 13.6% 84.1% 2.3% 0.0%14 14.3% 71.4% 14.3% 0.0%41 7.3% 90.2% 2.4% 0.0%133 5.3% 76.7% 18.0% 0.0%26 26.9% 57.7% 15.4% 0.0%32 21.9% 71.9% 6.3% 0.0%37 29.7% 62.2% 8.1% 0.0%9 11.1% 88.9% 0.0% 0.0% 88 13.6% 75.0% 1.1% 10.2%61 6.6% 83.6% 9.8% 0.0%552 10.9% 71.0% 14.9% 3.3%726 10.9% 72.7% 14.0% 2.3%251 9.6% 69.3% 21.1% 0.0%27 11.1% 81.5% 3.7% 3.7%21 19.0% 66.7% 14.3% 0.0%22 4.5% 90.9% 4.5% 0.0%52 15.4% 78.8% 5.8% 0.0%30 6.7% 80.0% 13.3% 0.0%10 20.0% 80.0% 0.0% 0.0%10 0.0% 90.0% 10.0% 0.0%10 0.0% 100.0% 0.0% 0.0%14 0.0% 100.0% 0.0% 0.0%28 7.1% 89.3% 3.6% 0.0%26 7.7% 84.6% 7.7% 0.0%25 24.0% 76.0% 0.0% 0.0%142 9.2% 89.4% 1.4% 0.0%78 47.4% 44.9% 7.7% 0.0%28 7.1% 92.9% 0.0% 0.0%37 0.0% 97.3% 2.7% 0.0%36 5.6% 91.7% 2.8% 0.0%21 0.0% 100.0% 0.0% 0.0%24 0.0% 100.0% 0.0% 0.0%35 17.1% 74.3% 8.6% 0.0%118 16.9% 79.7% 1.7% 1.7%109 35.8% 60.6% 3.7% 0.0%71 23.9% 70.4% 5.6% 0.0%73 8.2% 91.8% 0.0% 0.0%34 26.5% 67.6% 5.9% 0.0%26 30.8% 61.5% 7.7% 0.0%22 18.2% 59.1% 22.7% 0.0%26 26.9% 61.5% 11.5% 0.0%38 31.6% 55.3% 10.5% 2.6%41 51.2% 41.5% 7.3% 0.0%9 0.0% 66.7% 33.3% 0.0%17 5.9% 88.2% 5.9% 0.0%13 15.4% 61.5% 23.1% 0.0%22 4.5% 81.8% 13.6% 0.0%48 18.8% 70.8% 10.4% 0.0%49 16.3% 81.6% 2.0% 0.0%42 14.3% 83.3% 2.4% 0.0%37 10.8% 89.2% 0.0% 0.0%20 5.0% 95.0% 0.0% 0.0%30 13.3% 86.7% 0.0% 0.0%21 4.8% 85.7% 9.5% 0.0%12 8.3% 75.0% 16.7% 0.0%16 0.0% 100.0% 0.0% 0.0%17 17.6% 82.4% 0.0% 0.0%11 18.2% 81.8% 0.0% 0.0%15 6.7% 93.3% 0.0% 0.0%22 9.1% 68.2% 22.7% 0.0%29 6.9% 79.3% 13.8% 0.0%29 3.4% 93.1% 3.4% 0.0%26 19.2% 76.9% 3.8% 0.0%26 84.6% 0.0% 15.4% 0.0%10 10.0% 90.0% 0.0% 0.0%8 0.0% 75.0% 25.0% 0.0%12 25.0% 66.7% 8.3% 0.0%13 7.7% 84.6% 7.7% 0.0%12 16.7% 66.7% 16.7% 0.0%72 11.1% 80.6% 8.3% 0.0%105 13.3% 72.4% 14.3% 0.0%126 1.6% 98.4% 0.0% 0.0%124 4.0% 83.9% 10.5% 1.6%101 13.9% 80.2% 5.9% 0.0%166 11.4% 75.9% 7.2% 5.4%36 27.8% 72.2% 0.0% 0.0%38 26.3% 68.4% 5.3% 0.0%22 13.6% 68.2% 18.2% 0.0%38 7.9% 78.9% 10.5% 2.6%64 6.3% 92.2% 1.6% 0.0%10 0.0% 100.0% 0.0% 0.0%29 31.0% 69.0% 0.0% 0.0%37 29.7% 64.9% 5.4% 0.0%42 14.3% 81.0% 4.8% 0.0%61 16.4% 78.7% 4.9% 0.0%32 9.4% 81.3% 9.4% 0.0%66 91.0% 84.8% 9.1% 0.0%120 10.8% 80.8% 8.3% 0.0%121 14.9% 80.2% 5.0% 0.0%59 8.5% 81.4% 10.2% 0.0%72 9.7% 80.6% 9.7% 0.0%23 26.1% 43.5% 30.4% 0.0%17 41.2% 52.9% 5.9% 0.0%20 5.0% 90.0% 5.0% 0.0%32 12.5% 78.1% 9.4% 0.0%50 6.0% 88.0% 6.0% 0.0%21 4.8% 95.2% 0.0% 0.0%41 7.3% 92.7% 0.0% 0.0%114 25.4% 70.2% 4.4% 0.0%88 34.1% 56.8% 9.1% 0.0%143 7.0% 90.9% 0.7% 1.4%124 12.9% 83.9% 1.6% 1.6%113 9.7% 85.8% 4.4% 0.0%77 10.4% 88.3% 1.3% 0.0%28 21.4% 64.3% 14.3% 0.0%10 10.0% 20.0% 70.0% 0.0%69 23.2% 72.5% 4.3% 0.0%51 23.5% 68.6% 7.8% 0.0%17 11.8% 76.5% 11.8% 0.0%31 12.9% 87.1% 0.0% 0.0%25 28.0% 64.0% 8.0% 0.0%27 7.4% 88.9% 3.7% 0.0%24 4.2% 91.7% 4.2% 0.0%77 10.4% 80.5% 1.3% 7.8%81 18.5% 72.8% 8.6% 0.0%56 7.1% 82.1% 10.7% 0.0%104 7.7% 86.5% 5.8% 0.0%49 8.2% 89.8% 2.0% 0.0%64 12.5% 81.3% 6.3% 0.0%109 10.1% 85.3% 1.8% 2.8%36 11.1% 83.3% 5.6% 0.0%48 6.3% 93.8% 0.0% 0.0%38 28.9% 65.8% 5.3% 0.0%54 13.0% 79.6% 1.9% 5.6%17 11.8% 88.2% 0.0% 0.0% 72 41.7% 56.9% 1.4% 0.0%64 42.2% 46.9% 10.9% 0.0%74 16.2% 83.8% 0.0% 0.0%83 30.1% 62.7% 6.0% 1.2%44 2.3% 93.2% 4.5% 0.0%51 7.8% 84.3% 7.8% 0.0%50 6.0% 80.0% 14.0% 0.0%43 27.9% 65.1% 7.0% 0.0%39 17.9% 76.9% 5.1% 0.0%181 5.5% 87.3% 7.2% 0.0%157 10.2% 84.1% 5.7% 0.0%161 11.8% 83.9% 4.3% 0.0%167 7.2% 87.4% 5.4% 0.0%17 17.6% 82.4% 0.0% 0.0%9 0.0% 100.0% 0.0% 0.0%9 0.0% 88.9% 11.1% 0.0%61 4.9% 82.0% 6.6% 6.6%8 12.5% 87.5% 0.0% 0.0%44 22.7% 63.6% 13.6% 0.0%71 33.8% 45.1% 19.7% 1.4%17 5.9% 94.1% 0.0% 0.0%197 10.2% 69.5% 15.7% 4.6%156 7.7% 83.3% 9.0% 0.0%192 13.5% 73.4% 13.0% 0.0%145 9.0% 74.5% 14.5% 2.1%8 50.0% 50.0% 0.0% 0.0%4 50.0% 25.0% 25.0% 0.0%23 4.3% 91.3% 4.3% 0.0%24 8.3% 91.7% 0.0% 0.0%61 24.6% 63.9% 11.5% 0.0%74 18.9% 68.9% 10.8% 1.4%17 17.6% 76.5% 5.9% 0.0%16 31.3% 68.8% 0.0% 0.0%15 26.7% 73.3% 0.0% 0.0%169 17.2% 73.4% 9.5% 0.0%19 21.1% 73.7% 5.3% 0.0%17 17.6% 64.7% 17.6% 0.0%11 9.1% 81.8% 9.1% 0.0%42 14.3% 81.0% 4.8% 0.0%4 75.0% 0.0% 25.0% 0.0%6 100.0% 0.0% 0.0% 0.0%18 5.6% 94.4% 0.0% 0.0%27 25.9% 70.4% 3.7% 0.0%22 9.1% 81.8% 9.1% 0.0%17 17.6% 64.7% 17.6% 0.0%14 0.0% 100.0% 0.0% 0.0%123 13.8% 83.7% 2.4% 0.0%124 11.3% 83.9% 4.8% 0.0%126 21.4% 73.8% 4.8% 0.0%142 9.2% 83.1% 7.7% 0.0%64 3.1% 90.6% 6.3% 0.0%47 8.5% 89.4% 2.1% 0.0%9 0.0% 88.9% 11.1% 0.0%91 5.5% 91.2% 3.3% 0.0%137 5.1% 90.5% 4.4% 0.0%61 16.4% 82.0% 1.6% 0.0%30 10.0% 90.0% 0.0% 0.0%190 15.8% 66.8% 17.4% 0.0%121 16.5% 67.8% 15.7% 0.0%119 8.4% 89.9% 0.8% 0.8%47 8.5% 87.2% 4.3% 0.0%74 2.7% 90.5% 5.4% 1.4%21 9.5% 90.5% 0.0% 0.0%30 13.3% 83.3% 0.0% 3.3%28 17.9% 82.1% 0.0% 0.0%47 4.3% 87.2% 8.5% 0.0%64 35.9% 59.4% 4.7% 0.0%113 7.1% 88.5% 4.4% 0.0%16 12.5% 87.5% 0.0% 0.0%12 33.3% 50.0% 16.7% 0.0%35 5.7% 80.0% 14.3% 0.0%33 12.1% 84.8% 3.0% 0.0%23 4.3% 82.6% 13.0% 0.0%25 0.0% 84.0% 16.0% 0.0%7 14.3% 85.7% 0.0% 0.0%27 11.1% 88.9% 0.0% 0.0%40 7.5% 92.5% 0.0% 0.0%41 9.8% 90.2% 0.0% 0.0%41 12.2% 87.8% 0.0% 0.0%16 0.0% 100.0% 0.0% 0.0%17 0.0% 100.0% 0.0% 0.0%17 5.9% 88.2% 5.9% 0.0%38 15.8% 76.3% 7.9% 0.0%31 29.0% 58.1% 12.9% 0.0%198 6.1% 88.9% 5.1% 0.0%71 14.1% 84.5% 1.4% 0.0%26 23.1% 76.9% 0.0% 0.0%32 21.9% 78.1% 0.0% 0.0%11 0.0% 100.0% 0.0% 0.0%27 0.0% 85.2% 7.4% 7.4%41 9.8% 82.9% 7.3% 0.0%37 24.3% 70.3% 5.4% 0.0%12 8.3% 75.0% 16.7% 0.0%12 16.7% 66.7% 16.7% 0.0%9 0.0% 100.0% 0.0% 0.0%103 13.6% 78.6% 6.8% 1.0%114 24.6% 67.5% 7.9% 0.0%95 7.4% 87.4% 5.3% 0.0%15 6.7% 93.3% 0.0% 0.0%14 0.0% 100.0% 0.0% 0.0%50 2.0% 94.0% 4.0% 0.0%49 42.9% 49.0% 8.2% 0.0%22 50.0% 40.9% 9.1% 0.0%18 27.8% 66.7% 5.6% 0.0%19 42.1% 57.9% 0.0% 0.0%37 2.7% 94.6% 2.7% 0.0%31 0.0% 96.8% 3.2% 0.0%36 5.6% 94.4% 0.0% 0.0%112 8.9% 86.6% 4.5% 0.0%17 23.5% 70.6% 5.9% 0.0%30 16.7% 83.3% 0.0% 0.0%18956 13.5% 78.9% 6.9% 0.7%

20 21 female:pressureFACTS 2017

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