Gender differences and bias in open source: pull request acceptance of women versus men

Kabdo Choi, Hyunwoo Kim, Soyeon Jung

1 Contents

Gender difference and bias in STEM, CS, and open source community

Why it happens?

The effect of gender bias in open source community

Discussion

2 Gender difference and bias in STEM, CS, and open source community

3 Gender difference and bias in STEM

[1] [2]

[1] [2] Luke E. Holman, Devi E. Stuart-Fox, and Cindy E. Hauser. 2018. The gender gap in science: How long until women are equally represented? PLOS Biology 16, 4 (2018). DOI:http://dx.doi.org/10.1371/journal.pbio.2004956 4 Gender difference and bias in STEM

[3] [4] [5]

[3]C.A. Moss-Racusin, J.F. Dovidio, V.L. Brescoll, M.J. Graham, and J. Handelsman. 2012. Science faculty’s subtle gender biases favor male students. Proceedings of the National Academy of Sciences 109, 41 (2012), 16474–16479. DOI:http://dx.doi.org/10.1073/pnas.1211286109 [4]Silvia Knobloch-Westerwick, Carroll J. Glynn, and Michael Huge. 2013. The Matilda Effect in Science Communication. Science Communication 35, 5 (June 2013), 603–625. DOI:http://dx.doi.org/10.1177/1075547012472684 [5]Christine L. Nittrouer, Michelle R. Hebl, Leslie Ashburn-Nardo, Rachel C.E. Trump-Steele, David M. Lane, and Virginia Valian. 2017. Gender disparities in colloquium speakers at top universities. Proceedings of the National Academy of Sciences 115, 1 (2017), 104–108. DOI:http://dx.doi.org/10.1073/pnas.1708414115 5 Why gender diversity matters?

[6] [7]

[6] Bogdan Vasilescu et al. 2015. Gender and Tenure Diversity in GitHub Teams. Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems - CHI 15 (2015). DOI:http://dx.doi.org/10.1145/2702123.2702549 [7] Sander Hoogendoorn, Hessel Oosterbeek, and Mirjam Van Praag. 2013. The Impact of Gender Diversity on the Performance of Business Teams: Evidence from a Field Experiment. Management Science 59, 7 (2013), 1514–1528. DOI:http://dx.doi.org/10.1287/mnsc.1120.1674 6 Q : Whose pull requests would be more likely to get accepted in GitHub?

A : Women / Men / Almost same

7 Gender difference and bias in open source

Main RQ

To what extent does gender bias exist when pull requests are judged on GitHub?

Methodology

GHTorrent dataset on pull request from June, 7, 2010 to April 1, 2015 about pull request status, description, and comment

Linking GH accounts with social media profiles

Matching email address on the Google+ social network

Identify 1,426,127 (35.3%) of GH users’ gender

8 Gender difference and bias in open source

Result

women tend to have their pull requests accepted at a higher rate than men

Chart : acceptance rate of pull requests [8] Hypotheses

Do women’s pull request acceptance rates start low and increase over time?

Are women focusing their efforts on fewer projects?

Are women making pull requests that are more needed?

Are women making smaller changes?

Are women’s pull requests more successful when contributing code?

Is woman’s pull request accepted more often because she appears to be a women? Figure : Pull request acceptance rate over time. [8]

[8] Josh Terrell et al. 2017. Gender differences and bias in open source: pull request acceptance of women versus men. PeerJ Computer Science 3 (January 2017). DOI:http://dx.doi.org/10.7717/peerj-cs.111 9 Gender difference and bias in open source

Hypothesis

Do women’s pull request acceptance rates start low and increase over time?

Are women focusing their efforts on fewer projects?

Are women making pull requests that are more needed?

Are women making smaller changes?

Are women’s pull requests more successful when contributing code?

Is woman’s pull request accepted more often because she Figure : Pull request acceptance rate by gender and perceived gender [9] appears to be a women?

[9] Josh Terrell et al. 2017. Gender differences and bias in open source: pull request acceptance of women versus men. PeerJ Computer Science 3 (January 2017). DOI:http://dx.doi.org/10.7717/peerj-cs.111 10 Gender bias: Why?

11 Gender imbalance

Open source survey from GitHub[10], conducted in 2017 shows that 95% of the respondents were men, while only 3% of them were women.

22.6% of professional programmers in the U. S. are female[11].

[10] GitHub. 2017. Open Source Survey. Retrieved September 23, 2019 from https://opensourcesurvey.org/2017/ 12 [11] Klint Finley. 2019. Diversity in Open Source Is Even Worse Than in Tech Overall. (June 2017). Retrieved September 23, 2019 from https://www.wired.com/2017/06/diversity-open-source-even-worse-tech-overall/ What does the paper suggest?

Women’s PRs tend to make larger changes and to get accepted more than that of men’s

However, in cases of contribution from outsiders, acceptance rate was significantly lower for women

Survivorship bias: While going through formal and informal education in computer science, only more competent women remain till they can commit to open source while less competent men may continue

Women’s ratio in open source communities are significantly low, compared to that of programmers

13 Male-dominant and masculine community

Women were more likely to encounter unwelcome language (25% vs 15%), stereotyping (12% vs 2%),

and unsolicited sexual advances (6% vs 3%) compared to men [12].

“One event a group of men put print-outs of on sticks and carried them around. They approached women (and possibly men) to tell us that every time we use , Reiser will kill another woman.”

“A presenter had a title slide followed by a slide of bikini-clad women holding laptops, which he said was just to get people to pay attention. I'm not sure if we were supposed to pay attention to the women or to what he was saying though.”

"When strippers were hired to mix with people at the Saturday night event everyone attended, that made everyone uncomfortable." [13]

14 [12]GitHub. 2017. Open Source Survey. Retrieved September 23, 2019 from https://opensourcesurvey.org/2017/ [13]Valerie Aurora. 2019. The dark side of open source conferences (December 2010). Retrieved September 23, 2019 from https://lwn.net/Articles/417952/ Male-dominant and masculine community

Richard Stallman

Founder of GNU project

“Guru” of free software

Former president of Free Software Foundation and visiting scientist at MIT

[14]

15 [14]Ruben Rodriguez. 2019. , at LibrePlanet 2019. Retrieved September 23, 2019 from https://commons.wikimedia.org/wiki/File:Richard_Stallman_at_LibrePlanet_2019.jpg Male-dominant and masculine community

[15] [16]

[15]Jake Edge. 2018. A “joke” in the glibc manual. (November 2018). Retrieved September 23, 2019 from https://lwn.net/Articles/770966/ [16]Thomas Claburn. 2019. You have GNU sense of humor! Glibc abortion 'joke' diff tiff leaves Richard Stallman miffed. (May 2018). Retrieved September 23, 2019 from https://www.theregister.co.uk/2018/05/09/gnu_glic_abort_stallman/ 16 How does it affect the community?

17 [17]

[17]Nasif Imtiaz, Justin Middleton, Joymallya Chakraborty, Neill Robson, Gina Bai, and Emerson Murphy-Hill. 2019. Investigating the effects of gender bias on GitHub. In Proceedings of the 41st International Conference on Software Engineering (ICSE '19). IEEE Press, Piscataway, NJ, USA, 700-711. DOI: https://doi.org/10.1109/ICSE.2019.00079 18 Four Effects of Gender Bias

Prove-it-again

Stricter standard, has to provide more evidence to show competence

Tightrope

Narrower band of socially acceptable behavior

Maternal wall

Disadvantages to working mothers

Tug of war

Women discourage other women

19 Four Effects of Gender Bias in GitHub: Hypotheses

Prove-it-again: Stricter standard, has to provide more evidence to show competence → More description, push-back, signals of competence, and concentrated

Tightrope: Narrower band of socially acceptable behavior → More restraint in showing emotions

Maternal wall: Disadvantages to working mothers → Less displaying that they are parents

Tug of war: Women discourage other women → Women being especially harsh on other women

20 Four Effects of Gender Bias in GitHub: Results

Prove-it-again: Stricter standard, has to provide more evidence to show competence → More description, push-back, signals of competence, and concentrated

Tightrope: Narrower band of socially acceptable behavior → More restraint in showing emotions (less politeness/profanity, sentiment-neutral)

Maternal wall: Disadvantages to working mothers → Less displaying that they are parents

Tug of war: Women discourage other women → Women being especially harsh on other women

21 Gender bias exists, and it (at least partially) affects the open source community.

22 Discussion

How can we mitigate/overcome bias in OS?

- Inclusion & diversity in STEM (Ada Lovelace Day, Women in Open Source Awards, Django girls, …)

Other biases?

- E.g., gender (male, female, transgender, agender, ...), race, ethnicity, country

23