Coding like a girl - DjangoCon

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C O D I N G L I K E A G I R L

How teams with women gain with diversity

Gabriela D’Ávila

@gabidavila

A B O U T M E

• Major in Digital Game Development

• Senior Software Engineer with 8 years in the market

• Web Development

• Women in Technology Advocate

• Lego =)

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W H AT TO E X P E C T

• Diversity

• Bias

• Like A girl

• Diversity Reports

• How diversity is important

• Initiatives

3

D I V E R S I T Y

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D I V E R S I T Y

• Gender

• Racial

• Ethnic

• Sexual Orientation

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B I A S

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P R O J E C T I M P L I C I T ®

7http://implicit.harvard.edu/implicit

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P R O J E C T I M P L I C I T ®

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0% 7.5% 15% 22.5% 30%

1%

3%

6%

18%

18%

28%

26%Strong automatic association of Male with Science and Female with Liberal Arts

Moderate automatic association of Male with Science and Female with Liberal Arts

Slight automatic association of Male with Science and Female with Liberal Arts

Little to no association between genders and academic domains

Slight automatic association of Male with Liberal Arts and Female with Science

Moderate automatic association of Male with Liberal Arts and Female with Science

Strong automatic association of Male with Liberal Arts and Female with Science

Source: Project Implicit

2015

2014

L I K E A G I R L

10

11

"You know, you are pretty intelligent, for a girl. "

- Undisclosed friend

L I K E A G I R L

• You drive like a girl

• You punch like a girl

• You fight like a girl

• You [verb] like a girl

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D I V E R S I T Y R E P O R T S

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A L L A R E A S

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0%

20%

40%

60%

80%

100%

Apple Facebook Google Twitter

34%30%32%31%

66%70%68%69%

Male Female

Sour

ce:

Com

pani

es D

iver

sity

Rep

orts

0%

20%

40%

60%

80%

100%

Apple Facebook Google Twitter

30%30%31%30%

70%70%69%70%

Male Female

2015 2014

T E C H

15

0%

20%

40%

60%

80%

100%

Apple Facebook Google Twitter

13%18%16%21%

87%82%84%79%

Male Female

Sour

ce:

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pani

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iver

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orts

0%

20%

40%

60%

80%

100%

Apple Facebook Google Twitter

10%17%15%20%

90%83%85%80%

Male Female

2015 2014

N O N - T E C H

16

0%

20%

40%

60%

80%

100%

Apple Facebook Google Twitter

50%47%52%37%

50%53%48%63%

Male Female

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ce:

Com

pani

es D

iver

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Rep

orts

0%

20%

40%

60%

80%

100%

Apple Facebook Google Twitter

50%48%47%35%

50%52%53%65%

Male Female

2015 2014

H I G H L E V E L

17

0%

20%

40%

60%

80%

100%

Apple Facebook Google Twitter

22%22%23%28%

78%78%77%72%

Male Female

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iver

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Rep

orts

0%

20%

40%

60%

80%

100%

Apple Facebook Google Twitter

21%21%23%28%

79%79%77%72%

Male Female

2015 2014

T E C H W O R K F O R C E F A C T S

• Men 2.7x more chance of leading positions

• Women gravitates towards other women

• Lack of role models

• Women values flexibility more than men

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Source: Anita Borg Institute, Climbing the technical ladder

R A N K L E V E L S

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Source: Anita Borg Institute, Climbing the technical ladder

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Women Men

20.2%10.9%

55.2%56%

24.6%33.1%

Entry Mid High

W H Y D I V E R S I T Y M AT T E R S ?

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D I V E R S I T Y I N C R E A S E S G R O U P

P E R F O R M A N C E

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G R O U P P E R F O R M A N C E

• Collective Intelligence is increased

• Diverse teams are more efficient

• Better problem solving

• More innovative solutions

22Sour

ce:

Erne

st &

You

ng,

Prof

. An

ita W

illia

ms

Woo

lley,

Ani

ta B

org

Inst

itute

G R O U P P E R F O R M A N C E

• Three factors: Proportion of females on the group Social sensitivity Numbers of speaking members

23

Sour

ce:

Erne

st &

You

ng,

Prof

. An

ita W

illia

ms

Woo

lley,

Ani

ta B

org

Inst

itute

D I V E R S I T Y P O W E R S I N N O V AT I O N

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I N N O V AT I O N

• Competitive advantage

• Diverse groups outstanding performance

• Patents with mixed gender cited more often

25Sour

ce:

Erne

st &

You

ng,

Prof

. An

ita W

illia

ms

Woo

lley,

Ani

ta B

org

Inst

itute

26

I N N O V AT I O N

26Source: London Business School, Anita Borg Institute

"If people think alike, then no matter how smart they are they most likely will get stuck at the same locally optimal solutions. Innovating, requires thinking

differently. That's why diversity powers innovation."

–Scott Page, University of Michigan

I N N O V AT I O N

27Source: London Business School, Anita Borg Institute

N E I L D E G R A S S E T Y S O N

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N E I L D E G R A S S E T Y S O NAstrophysicist

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“Before we start talking about genetic differences, you got to come up with a system that is equal opportunity. Then

we can have that conversation.” – Neil deGrasse Tyson, at 2009 New York Conference - Link

H O W C A N I H E L P ?

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T H E C O D E M A N I F E S TO

• Discrimination limits us

• Boundaries honor us

• We are our biggest assets

• We are resources for the future

• Respect defines us

• Reactions require grace

• Opinions are just that: opinions

• To err is human

32http://www.codemanifesto.com

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P R O G R A M S

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Q U E S T I O N S ?

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T H A N K YO U

• Twitter: @gabidavila

• Web: http://gabriela.io

• Email: gabidavila@gmail.com

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R E F E R E N C E S• ANITA BORG INSTITUTE - Climbing the Technical Ladder

• ANITA BORG INSTITUTE - The Case for Investing on Women

• ANITA BORG INSTITUTE - Women Technologists Count

• ANITA WOLLEY - Evidence for a Collective Intelligence Factor in the Performance of Human Groups

• CATALYST, Why Diversity Matters?

• ERNST & YOUNG - Groundbreakers

• ILLUMINATE VENTURES - High Performance Entrepreneurs

• CODE MANIFESTO - Website

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