How to Visualize Data Effectively to PromoteDiversity and Inclusion

Yusaku Horiuchi (Dartmouth) In Song Kim (MIT)

APSA 2018

August 31, 2018

Horiuchi (Dartmouth) and Kim (MIT) Data Visualization Hackathon, APSA 2018 1 / 13

1 Hackathon: Data Visualization Team

2 Team Outputs

Suggested Datasets1 A replication package of Teele and Thelen (2018)https://www.dropbox.com/s/6v2sqzej2q4ifg0/2017_Teele_Thelen_Replication.zip?dl=0

2 A replication package of Carey et al (2018, forthcoming)https://doi.org/10.7910/DVN/GD1UEI

3 A replication package of Htun et al (2018, forthcoming)https://www.dropbox.com/sh/8mw8qocqx1r1d2g/AACtxWwVoYOf6IoUyknhlg4Ca?dl=0

4 College Scorecardhttps://collegescorecard.ed.gov/data/

5 National Center for Education Statisticshttps://nces.ed.gov/datatools/

6 Variety of Democracy (V-Dem) datasethttps://www.v-dem.net/en/data/data-version-8/

7 Quality of Government datasethttps://qog.pol.gu.se/data

Horiuchi (Dartmouth) and Kim (MIT) Data Visualization Hackathon, APSA 2018 2 / 13

InstructionsParticipants may either use the provided datasets or bring theirown to produce visualizations

Please submit your output as yourlastname.zip with the folderstructure described belowhttps://www.dropbox.com/sh/c4xpvaeminf7whw/AACTqsXsk8f7ZVHbemjgEjJUa?dl=0

Your folder structure1 /code/2 /data/3 /figure/

Horiuchi (Dartmouth) and Kim (MIT) Data Visualization Hackathon, APSA 2018 3 / 13

1 Hackathon: Data Visualization Team

2 Team Outputs

Participants

Yusaku Horiuchi (Dartmouth College)

In Song Kim (MIT)

Basak Traktas (Northwestern University)

Francesca Jensenius (University of Oslo)

Katherine Clayton (Dartmouth College )

John Carey (Dartmouth College)

Tom Paskhalis (London School of Economics)

Selina Hofstetter (London School of Economics)

Jim Cupples (NationBuilder)

Horiuchi (Dartmouth) and Kim (MIT) Data Visualization Hackathon, APSA 2018 4 / 13

Gender Gaps in Perceptions about Publication in PA

−0.427**−0.427**(0.139)(0.139)

+0.038+0.038(0.094)(0.094)

−0.388**−0.388**(0.126)(0.126)

+0.091+0.091(0.128)(0.128)

Likelihood of Submitting

Quantitative

Likelihood of Submitting

Qualitative

Likelihood of Publishing

Quantitative

Likelihood of Publishing

Qualitative

Man Woman Man Woman Man Woman Man Woman

Very unlikely

Somewhat unlikely

Neither likely nor unlikely

Somewhat likely

Very likely

Horiuchi (Dartmouth) and Kim (MIT) Data Visualization Hackathon, APSA 2018 5 / 13

Women’s Political Empowerment Over Time

Russia Turkey

Iran Japan Norway

Belgium China Germany

1900 1925 1950 1975 2000 1900 1925 1950 1975 2000

1900 1925 1950 1975 2000

0.25

0.50

0.75

1.00

0.25

0.50

0.75

1.00

0.25

0.50

0.75

1.00

Year

Wom

en p

oliti

cal e

mpo

wer

men

t ind

ex

Horiuchi (Dartmouth) and Kim (MIT) Data Visualization Hackathon, APSA 2018 6 / 13

Happiness isn’t associated with political empowerment

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Malaysia (1966−)

Mexico

Egypt

Uzbekistan

Not at all happy

Not very happy

Rather happy

Very happy

0.4 0.6 0.8

Women political empowerment index (V−DEM)

Fee

ling

of h

appi

ness

(W

orld

Val

ue S

urve

ys)

Horiuchi (Dartmouth) and Kim (MIT) Data Visualization Hackathon, APSA 2018 7 / 13

Sexual harassment training at UNM: Effects on sexism

0.30 0.35 0.40 0.45 0.50 0.55

0.20

0.25

0.30

0.35

0.40

0.45

0.50

Effect of training men respondents

Benevolent sexism score (0−1)

Hos

tile

sexi

sm s

core

(0−

1)

0.30 0.35 0.40 0.45 0.50 0.55

0.20

0.25

0.30

0.35

0.40

0.45

0.50

Effect of training women respondents

Benevolent sexism score (0−1)H

ostil

e se

xism

sco

re (

0−1)

BlackHispanicNativeOtherWhite

N=50

●N=10

Benevolent sexism, e.g., “women should be rescued first”Hostile sexism, e.g., “women are too easily offended”

Horiuchi (Dartmouth) and Kim (MIT) Data Visualization Hackathon, APSA 2018 8 / 13

Contents of Lobbying:American Association of University Women

Horiuchi (Dartmouth) and Kim (MIT) Data Visualization Hackathon, APSA 2018 9 / 13

Finacial Flow and Politicians

Horiuchi (Dartmouth) and Kim (MIT) Data Visualization Hackathon, APSA 2018 10 / 13

Ethnic Composition and Earning

0.00

0.25

0.50

0.75

1.00

5th 10th 15th 20th 25th 30th 35th 40th 45th 50th 55th 60th 65th 70th 75th 80th 85th 90th 95th

Earnings by percentile

Per

cent

of s

tude

nt p

opul

atio

n by

rac

e/et

hnic

ity

Race

Asian

Black

Hispanic

White

Racial/ethnic composition of student populations by income, 10 years after enrollment

Horiuchi (Dartmouth) and Kim (MIT) Data Visualization Hackathon, APSA 2018 11 / 13

Voter Composition

Louisiana Registered Voters Louisiana OfficeholdersWhite Voters 1886758 White Officeholders 3312Black Voters 923866 Black Officeholders 1054Other & N/A Officeholders 148360 Other & N/A Officeholders 206

Louisiana Registered Voters Louisiana OfficeholdersMen 1330162 Men 3255Women 1628135 Women 1150Other & N/A Voters 687 Other & N/A Voters 185

Horiuchi (Dartmouth) and Kim (MIT) Data Visualization Hackathon, APSA 2018 12 / 13

Rate Professors!

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3

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1 2 3 4 5Easyness of professor's taught course

Ave

rage

ove

rall

qual

ity o

f rat

ed p

rofe

ssor

Gender

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femalemale

Horiuchi (Dartmouth) and Kim (MIT) Data Visualization Hackathon, APSA 2018 13 / 13