Drupalcon Portland 2013 - Programming Diversity

Drupalcon Portland 2013 - Programming Diversity

It's been scientifically proven that more diverse communities and workplaces create better products and the solutions to difficult problems are more complete and diverse themselves. Companies are struggling to find adequate talent. So why do we see so few women, people of color, and LGBTQ people at our events and on the about pages of our websites? Even more curiously, why do 60% of women leave the tech industry within 10 years? Why are fewer women choosing to pursue computer science and related degrees than ever before? Why have stories of active discouragement, dismissal, harassment, or worse become regular news?

In this talk we’ll examine the causes behind the lack of diversity in our communities, events, and workplaces. We’ll discuss what we can do as community members, event organizers, and co-workers to not only combat this problem, but to encourage positive change by contributing to an atmosphere of inclusivity.

Objectives:
-Educate about the lack of diversity and why it is a problem
-Examine what is contributing to both the pipeline issue as well as attrition
-Isolate what is and isn't working
-Inspire direct action by examining our own behavior and learning more about the people around us so we can empathize better

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Ashe Dryden

May 21, 2013
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Transcript

  1. @ashedryden Programming Diversity

  2. @ashedryden Ashe Dryden @ashedryden ashedryden.com

  3. @ashedryden What is Diversity?

  4. @ashedryden more than gender

  5. @ashedryden various backgrounds, experiences, and lifestyles

  6. @ashedryden not always visible

  7. @ashedryden race gender sexuality ability language appearance physical & mental

    health age socioeconomic class and more!
  8. @ashedryden Intersectionality the interactions of biological, social, and cultural traits

    contributing to systemic inequality
  9. @ashedryden race gender ability physical & mental health socioeconomic class

  10. @ashedryden in the US, women on average earn 80.9% of

    what men do Source: ABC: How to end the wage gap between men and women, http:/ /abcnews.go.com/ABC_Univision/News/women- make-men/story?id=18702478#.UZt3yitASqk
  11. @ashedryden but Latina women earn 59.3% of what white men

    do Source: ABC: How to end the wage gap between men and women, http:/ /abcnews.go.com/ABC_Univision/News/women- make-men/story?id=18702478#.UZt3yitASqk
  12. @ashedryden the unemployment rate in the US is ~7.5% Source:

    High Rate of Unemployment for the Blind, http:/ / work.chron.com/high-rate-unemployment-blind-14312.html
  13. @ashedryden the unemployment rate for the blind is 70-75% Source:

    High Rate of Unemployment for the Blind, http:/ / work.chron.com/high-rate-unemployment-blind-14312.html
  14. @ashedryden Privilege unearned advantages a person gets for a perceived

    trait they possess, putting them in the “normal” group
  15. @ashedryden Better Education Access to Technology at an Earlier Age

    Higher Pay Assumed Competency Quality of Social/Professional Network Seen as Skill Set Instead of Traits Easily Fit Into/Identify with Subculture
  16. @ashedryden Stereotype Threat anxiety or concern where a person has

    the potential to confirm a negative stereotype about their social group
  17. @ashedryden Source: xkcd, How it Works: http:/ /xkcd.com/385/

  18. @ashedryden Impostor Syndrome a psychological phenomenon in which people are

    unable to internalize their accomplishments
  19. @ashedryden this is especially pronounced when negative stereotypes exist about

    a group a person is in
  20. @ashedryden less likely to apply for certain jobs

  21. @ashedryden less likely to submit a talk to a conference

  22. @ashedryden less likely to attend to a conference

  23. @ashedryden Marginalized Someone pushed to the edge of a group

    and accorded lesser importance; a minority or sub- group being excluded, their needs or desires being ignored.
  24. @ashedryden society teaches us to do this to everyone within

    marginalized groups
  25. @ashedryden “I’m different. I’m logical and rational; I don’t see

    gender or race.”
  26. @ashedryden Source: Moss-Racusin, et al. Science faculty’s subtle gender biases

    favor male students, 2012 scientists & STEM professors do this to other scientists & STEM professors
  27. @ashedryden even marginalized people do it to people within their

    same social groups
  28. @ashedryden How diverse is the tech industry?

  29. @ashedryden Women make up 24% of the industry Source: FLOSSPOLS

    - Gender Integrated Report Findings
  30. @ashedryden ...but only 1.5-3% of OSS contributors Source: FLOSSPOLS -

    Gender Integrated Report Findings
  31. @ashedryden how many women contribute to drupal?

  32. @ashedryden we don’t know.* * we know about 17% attend

    DrupalCon
  33. @ashedryden Source: Mercury News. Blacks, Latinos, and Women lose ground

    in tech companies, 2011 Women Hispanic Black Asian White 0% 25% 50% 75% 100% Tech Industry US Population Tech Industry vs US Population
  34. @ashedryden Lack of Diversity is a Global Problem

  35. @ashedryden India 8% of CS students Source: Anita Borg Institute,

    State of Women in Technology Fields Around the World
  36. @ashedryden US 17% of CS students Source: Anita Borg Institute,

    State of Women in Technology Fields Around the World
  37. @ashedryden UK 18.2% of CS students Source: Anita Borg Institute,

    State of Women in Technology Fields Around the World
  38. @ashedryden France 20% of CS students Source: Anita Borg Institute,

    State of Women in Technology Fields Around the World
  39. @ashedryden Brazil 20% of CS students Source: Anita Borg Institute,

    State of Women in Technology Fields Around the World
  40. @ashedryden South Africa 25% of CS students Source: Anita Borg

    Institute, State of Women in Technology Fields Around the World
  41. @ashedryden “Maybe women just aren’t interested in programming.”

  42. @ashedryden “Or maybe women aren’t biologically predisposed to programming.”

  43. @ashedryden there exists no physical or biological difference that impacts

    a person’s ability to be a programmer
  44. @ashedryden the differences that exists are purely social and cultural

    constructs, and are therefore able to be overcome
  45. @ashedryden Bulgaria 73% of CS students Source: Anita Borg Institute,

    State of Women in Technology Fields Around the World
  46. @ashedryden Diversity Matters

  47. @ashedryden Diversity Matters to businesses

  48. @ashedryden sales revenue, number of customers, market share, and profits

    relative to competitors increase Source: Does Diversity Pay?, Cedric Herring, AMERICAN SOCIOLOGICAL REVIEW, 2009, VOL. 74 (April:208–224)
  49. @ashedryden solve complex problems better and faster Source: Scott Page,

    The difference: How the power of diversity creates better groups, firms, schools, and societies. Princeton University Press, 2009
  50. @ashedryden more creative & stimulated through persistent exposure to minority

    perspectives Source: Charlan Jeanne Nemeth, Differential Contributions of Majority and Minority Influence.
  51. @ashedryden make better decisions, generate more innovation Source: Caroline Simard,

    Ph.D., Obstacles and Solutions for Underrepresented Minorities in Technology, at 8, Anita Borg Institute for Women and Technology (2009)
  52. @ashedryden the financial success and viability of a company are

    directly related to the makeup of its teams
  53. @ashedryden Diversity Matters to society

  54. @ashedryden heal the issue of unequal pay and opportunity

  55. @ashedryden create class mobility

  56. @ashedryden the wage gap is smaller in STEM fields

  57. @ashedryden in tech women earn about 87% of what men

    do
  58. @ashedryden Why the lack of diversity?

  59. @ashedryden Pipeline

  60. @ashedryden Cultural Cues

  61. @ashedryden difference in toys and games for boys and girls

  62. @ashedryden no famous role models that represent them

  63. @ashedryden Access to Technology

  64. @ashedryden on average, men get access to their first computer

    at 11
  65. @ashedryden women get access to their first computer at 14

  66. @ashedryden African American and Hispanic households have lower computer ownership

    rates and broadband adoption
  67. @ashedryden African American and Hispanic are adopting smart phones at

    a much higher rate than their white counterparts
  68. @ashedryden Access to Quality Education

  69. @ashedryden quality high school education is one of the greatest

    indicators of earning potential
  70. @ashedryden schools in poor neighborhoods have lower quality math and

    science programs
  71. @ashedryden Access to healthcare

  72. @ashedryden women are more likely to be caregivers

  73. @ashedryden people of color, people with disabilities, and LGBTQ people

    have less access to quality healthcare
  74. @ashedryden Attraction

  75. @ashedryden Lack of Role Models

  76. @ashedryden less likely to see people like them represented in

    companies and conferences
  77. @ashedryden Geek Stereotype

  78. @ashedryden people who don’t identify and aren’t represented by the

    geek stereotype are turned off by impression of someone who represents the stereotype Source: Enduring Influence of Stereotypical Computer Science Role Models on Women’s Academic Aspirations, Cheryan 2012
  79. @ashedryden Attrition

  80. @ashedryden 56% of women leave tech within 10 years Source:

    NCWIT, 2012
  81. @ashedryden that’s twice the attrition rate of men

  82. @ashedryden harassment

  83. @ashedryden people in a marginalized group are twice as likely

    to report being harassed or mistreated
  84. @ashedryden “I’ve never seen someone get harassed.”

  85. @ashedryden discrimination

  86. @ashedryden pay, advancement, job offers

  87. @ashedryden men are 2.7 times more likely than women to

    be promoted to a high-ranking job, such as vice president or senior manager Source: Mercury News 2010, http:/ /www.mercurynews.com/ ci_14382477
  88. @ashedryden Myriad Solutions

  89. @ashedryden Change Starts with Us

  90. @ashedryden Education is the Trojan Horse to Empathy

  91. @ashedryden Get to know people different than us

  92. @ashedryden Understand that bias and discrimination are often subtle

  93. @ashedryden Learn to Apologize

  94. @ashedryden Advocate for Change

  95. @ashedryden Talk about these issues openly

  96. @ashedryden “That’s not cool :(”

  97. @ashedryden Influence change in our communities and workplaces

  98. @ashedryden Have the hard conversations

  99. @ashedryden Increase Education and Access

  100. @ashedryden help facilitate events for marginalized people in tech

  101. @ashedryden volunteer at local schools and groups

  102. @ashedryden commit financial resources

  103. @ashedryden work with colleges and universities

  104. @ashedryden “What are you doing to help students who’ve had

    less exposure to technology?”
  105. @ashedryden remove bias from our schools and universities

  106. @ashedryden “Have you programmed before?”

  107. @ashedryden Change Our Workplaces

  108. @ashedryden what does the ‘about’ page of your website look

    like?
  109. @ashedryden vocal support

  110. @ashedryden job listing language and requirements

  111. @ashedryden benefits

  112. @ashedryden interviewing

  113. @ashedryden equal pay

  114. @ashedryden culture

  115. @ashedryden mentoring and career goal attainment

  116. @ashedryden Improve Inclusion at Conferences

  117. @ashedryden diversity in the organizing team

  118. @ashedryden work with the community

  119. @ashedryden codes of conduct

  120. @ashedryden scholarships

  121. @ashedryden anonymized proposal processing

  122. @ashedryden outreach

  123. @ashedryden there is no silver bullet

  124. @ashedryden multi-faceted problems require multi-faceted solutions

  125. @ashedryden requires participation from everyone

  126. @ashedryden Questions?

  127. @ashedryden Thank You! feedback bit.ly/ashe-PDX resources bit.ly/ashe-help