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Get quick access to featured resources from the Kapor Center and Reveal News.


Better Decisions Through Diversity explains how heterogeneity can boost group performance.

Breaking the Mold: Investing in Racial Minorities in Tech (2017) underscores the business case for racial diversity and explores the systemic problem of racial bias in tech; the failure of existing efforts to effectively address the problem; and the powerful role of investors in holding tech companies accountable for real change.

Decoding Diversity: Financial and Economic Returns of Diversity in Tech (2016) presents an analysis of the economic impact of improving diversity in the technology sector, based on diversity data from nearly 170 companies, and shows correlations between more diverse tech company workforces and higher revenues, profits, and market value.

Diversity Matters (2015) examines the relationship between the level of diversity and company financial performance.

Do Pro‐Diversity Policies Improve Corporate Innovation? (2017, abstract only) finds a causal link between diversity and innovative products and services.

Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification (2018) presents an approach to evaluate bias present in automated facial analysis algorithms and datasets with respect to phenotypic subgroups. Using the Fitzpatrick Skin Type classification system, authors characterize the gender and skin type distribution of two facial analysis benchmarks, IJB-A and Adience.

What is the impact of gender diversity on technology business performance (2014)?  reviews research on gender-diverse teams and strategies to maximize the potential benefits of gender diversity on technical teams.

Where Did You Go to School? offers demographic stats on venture capitalists and identifies that 40% of VCs attended either Harvard or Standford. (Medium, 7/30/18)

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Atlassian State of Diversity Report (2018) surveyed more than 1,400 tech workers to understand how tech employees perceive diversity progress within their industry, and in light of the current socio-political climate.

Black and Hispanic underrepresentation in tech: Its time to change the equation (2018) draws on data to describe the state of tech workforce demographics by race.

Dice Diversity and Inclusion Report (2018) explores trends in tech by gender, age, LBGTQ, political affiliation.

Diversity Gaps in Computer Science: Exploring the Underrepresentation of Girls, Blacks and Hispanics (2016) raises awareness about structural and social barriers for the target groups in computer science, based on student parent, teacher, principal, and superintendent surveys.

Diversity in IT (2017), a report of the British Computer Society, addresses minority representation in IT professionals, explores the extent to which the market is failing those from minority groups, and highlights potential benefits of working in IT that may be enjoyed by anyone with an interest or aptitude  for such work.

Diversity in Tech (2016) offers an employee breakdown of key technology companies.

Diversity in the High Tech Industry (2018), a CompTIA report, explores the state of diversity in the tech industry and offers a series of contradictory viewpoints on the current state and future goals for workplace diversity.

From Consumers to Creators: The Digital Lives of Black Consumers (2018) shows how brands, companies and advertisers can make connections with Black consumers, who show an affinity for all things digital.

Gender Differences in Entrepreneurship (2018) uses data to compare the experiences of female and male entrepreneurs.

Girls and Women of Color in Computing (2018)  provides data to explain the state of girls and women of color across the computing pipeline.

Global Human Capital Trends (2014) examines the priorities and preparedness of executives and HR professionals around the world, and to provides insight on what it takes to move from diversity to inclusion.

Here’s the clearest picture of Silicon Valley’s diversity yet: It’s bad. But some companies are doing less bad (2018) offers a detailed picture of diversity and inclusion in tech and allows those that are public to be compared with all their peers.

Hidden in Plain Sight: Asian American Leaders in Silicon Valley (2015) uses data released by five large Silicon Valley companies to analyze the number of employees in the pipeline of management classifications by gender and race.

Implicit Bias Review (2017) highlights key selections from the academic literature on implicit bias published in 2016 as it pertains to employment, education, and other domains and also highlights implicit bias mitigation strategies and other major contributions to the field.

In Collaborative Work Cultures, Women Carry More of the Weight (2018) used surveys, interviews and direct observation to understand how decisions to invest time on collaborative tasks can impact time spent on priority tasks and perception of colleagues.

Information Gap, Not Pipeline, Behind Low Diversity Numbers in Tech (2017) demonstrates that a lack of career information and exposure – not a pipeline problem – that is preventing underrepresented minorities majoring in STEM and non-STEM from pursuing careers in tech.

Is Silicon Valley Tech Diversity Possible Now? (2018) examines diversity in the Tech industry by calculating executive, managerial and professional employment shares by race and gender for leading Silicon Valley Tech firms, comparing them to 1,277 smaller Tech firms.

The Leaky Tech Pipeline: A Comprehensive Framework for Understanding and Addressing the Lack of Diversity across the Tech Ecosystem (2018) introduces the Leaky Tech Pipeline Framework, explores data on underrepresentation and barriers to diversity, and provides a roadmap for comprehensive interventions and solutions to increase racial and gender diversity across the tech ecosystem.

The governance divide: Boards and investors in a shifting world (2017) presents findings from PwC’s 2017 Annual Corporate Directors Survey which examines the areas where directors and investors are aligned and moving forward together, as well as the ways in which they are out of sync.

Male Advocates and Allies: Promoting Gender Diversity in Technology Workplaces (2013) draws on interviews with 47 men in technical companies and departments to 1) identify factors that motivate or hinder men in advocating for gender diversity, 2) explore what diversity efforts men have experienced as successful or unsuccessful, and 3) identify specific strategies to increase men’s participation in advocacy.

National Urban League 2018 Digital Inclusion Index (2018) identifies the extent to which the new job, business and educational opportunities created by increased digitization of our world is equally shared using three values: digital skills and occupations (35%), digital access (35%) and digital policy (30%).

New Ideas for a Diverse America (2011) describes the demographic changes our nation will experience over the next four decades and argues that a progressive vision is urgently needed to ensure we take advantage of diversity as one of our greatest assets.

Open Diversity Data lists tech and other companies that have and have not released\ corporate diversity and EEO-1 reports.

Puncturing the pipeline: Do technology companies alienate women in recruiting sessions? (2018) used original observational data from 84 recruiting sessions hosted by technology companies at a prominent university on the US West Coast and found that company representatives often engage in behaviors that are known to create a chilly environment for women.

Research: The Average Age of a Successful Startup Founder Is 45 (2018) found that the top 0.1% of startups based on growth in their first five years were founded by individuals who averaged 45 years of age.

Solving the Equation: The Variables for Women’s Success in Engineering and Computing (2015) explores the significant under-representation of women in engineering and computing and explains what can be done to make these fields open to and desirable for all employees.

State of Salaries Report (2018) examines 2017 data on technology workers to answer the questions: What impact do race and age have on my pay? How does my salary stack up against my coworkers’? Would my salary go further if I relocated? Which industries and companies are paying the most?

The State of Wage Inequality in Tech in 2018 reports the racial wage gap in tech.

Tech Alliance Report (2018) highlights the current lack of diversity in tech showing significant lack of senior women across the sector, while black, Asian and Minority Ethnic (BAME) leaders are underrepresented compared to the wider population.

Tech Leavers Study (2017) explores why people voluntarily leave jobs in tech and found that workplace culture drives turnover, significantly affecting the retention of underrepresented groups, and costing the industry more than $16 billion each year.

Tech’s Invisible Workforce (2016) highlights the contributions of tech’s contract workforce and the inequities that workers face.

The 2017 Global Information Security Workforce Study: Women in Cybersecurity highlights the state of women in cybersecurity.

The Global Gender Gap Report 2017 benchmarks 144 countries on their progress towards gender parity across four thematic dimensions: Economic Participation and Opportunity, Educational Attainment, Health and Survival, and Political Empowerment.

The Illusion of Asian Success: Scant Progress for Minorities in Cracking the Glass Ceiling from 2007–2015 presents EEOC data showing that despite the increase in their numbers as executives, Asians are still the least upwardly mobile demographic to reach leadership positions in Bay Area technology companies.

The Latest Research Diversity (2016) presents a collection of Harvard Business Review articles on gender, race, LGBT issues, and cross- cultural concerns.

The State of Diversity and Funding in the Non Profit Tech Sector (2018) is the first report that examines diversity in the non profit tech space.

There Is a Supply of Diverse Workers in Tech, So Why Is Silicon Valley So Lacking in Diversity? (2017) uses empirical data to correct three myths that are commonly used to explain away or minimize the lack of diversity in Silicon Valley. It also highlights some of the most promising, tested solutions to date.

Tilted Playing Field: Hidden Bias in IT (2011) reveals that hidden biases within the workplace can produce unequal opportunities and outcomes for employees depending on their race and gender.

One Step Forward, One Step Back: White Male Top Manager Organizational Identification and Helping Behavior toward Other Executives Following the Appointment of a Female or Racial Minority CEO (2018) found that following the appointment of a female or racial minority CEO, white male top managers tend to experience a diminished sense of organizational identification, and in turn provide less help to colleagues, with this reduction particularly pronounced for help provided to minority status colleagues.

Revolutionizing the STEM Entrepreneurship Ecosystem (2018) outlines the systemic entrepreneurship barriers to opportunity and access for women in STEM, and also provides actionable recommendations for businesses, investors, and entrepreneurship support programs to expand funding opportunities, increase diversity and cultivate gender equity in STEM.

`Very Lonely.’ The Unsettling Hum of Silicon Valley’s Failure to Hire More Black Workers (2018). Bloomberg’s analysis of tech industry demographic data found that among eight large firms, the portion of black employees in technical roles has risen less than a percentage point since 2014.

Women and Men in STEM Often at Odds Over Workplace Equity (2017) addresses the prevalence of gender discrimination and harassment in STEM fields.

Women in the Workplace (2018) is the largest comprehensive study of the state of women in corporate America. The report is published by LeanIn.Org and McKinsey & Company.

Women Who Choose Computer Science (2014) examines factors that influence young women’s decisions to pursue degrees in computer science.

Women, Minorities, and Persons with Disabilities in Science and Engineering (2017) provides statistical information about women, minorities, and persons with disabilities in science and engineering.

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Dear Tech People uses data to rank race and gender diversity at 100 top tech companies.

Diversity List explores gender and race diversity in fast growing technology companies by collecting diversity data from company team pages or Angellist and rank ordering them. is a collection of diversity reports from top companies.

Hidden Figures: How Silicon Valley Keeps Diversity Data Secret (2017) addresses how Reveal from The Center for Investigative Reporting compiled data from Silicon Valley tech companies that publicly released their government-mandated EEO-1 reports for 2016. Reveal also shows data on female employees in Silicon Valley by race.

SV 150: Rankings of the Top 150 Public Tech Companies in the Bay Area (2016) ranks Silicon Valley’s top public tech companies in everything from sales to taxes paid.

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Black Women Business Startups (2018) offers insight on policy and programing to accelerate and expand the economic impact black women business owners in their local economies.

Crunchbase Women in Venture Report (2017) determines the number of women who are investing partners at the 100 top venture and micro-venture firms. It also reveals which venture and micro-venture firms have the strongest track record of supporting startups with at least one female co-founder.

Gender Differences in Entrepreneurship: Voices of Founders and Funder (2018) offers research on how women and male founders view entrepreneurship, from why they do it to how much support they receive from family members.

Global Venture Funding Going To Female Founders Skyrockets, But There’s A Catch (2018) examines venture and seed global investment trends in female-founded startups over five quarters.

Male and Female Entrepreneurs Get Asked Different Questions by VCs — and It Affects How Much Funding They Get (2017) offers evidence as to why female entrepreneurs continue to receive less funding than their male counterparts.

National Venture Capital Association -Deloitte Human Capital Survey Report (2016) reveals findings from a study on the prevalence of women and minorities in senior investment roles at venture capital firms. There is also a companion interactive dashboard to drill deeper into the survey results.

Project Diane  is a biennial demographic study authored by digitalundivided that provides a snapshot of the state of Black Women Founders, and the startups they lead, in the United States.

Q1 2018 Global Diversity Investment Report: Investing Trends in Female Founders (2018) examines venture and seed investment trends in female-founded startups over the last five quarters, examining more than 9,119 venture deals and 6,802 seed deals for companies with founders associated.

Startup Financing Trends by Race: How Access to Capital Impacts Profitability (2016) explores startup financing trends and how access and cost of capital impact profitability using data from the Annual Survey of Entrepreneurs (ASE).

The Color of Entrepreneurship: Why the Racial Gap among Firms Costs the U.S. Billions (2016) documents the changes in the economic status of businesses owned by people of color between 2007 and 2012.

The 2018 State of Women-Owned Businesses Report commissioned by American Express OPEN tracks data on the state of women and entrepreneurship.

The Leaky Tech Pipeline: a Comprehensive Framework for Understanding and Addressing the Lack of Diversity across the Tech Ecosystem (2018) introduces the Leaky Tech Pipeline Framework, explores data on underrepresentation and barriers to diversity, and provides a roadmap for comprehensive interventions and solutions to increase racial and gender diversity among entrepreneurs and across the tech ecosystem.

The United States Of Startups: The Most Well-Funded Tech Startup In Every US State (2018) uses the CB Insights database to identified the most-well funded VC-backed technology startups by state based on disclosed equity funding.

What’s it like to be a female tech entrepreneur? (2018) presents findings from a pilot survey understand the experiences female founders in raising venture funding for their startups—specifically in relation to subtle and overt inappropriate behaviors including comments, assumptions, rudeness, and bullying and harassment.

Why Women-Owned Startups Are a Better Bet (2018) examines success experienced by female founders.

Women Entrepreneurship Report (2018) presents findings from Inc., and Fast Company’s survey of female founders to fully understand the female entrepreneurial experience in 2018.

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2016 National Council on Disability Report to the White House and Congress focuses on disability, technology, and policy.

CBC TECH 2020 Year in Review Increasing America’s Global Competitiveness by Advocating for African American Inclusion at all levels of the Technology Industry highlights the work of CBC Tech 2020 over the past year and includes our key principles, focus areas, findings from several meetings with key stakeholders from across the country, and highlights of companies who have taken the pledge as well as specific policy recommendations from CBC Members.

Diversity in the Tech Sector: Federal Agencies Could Improve Oversight of Equal Employment Opportunity Requirements (2017) examines (1) trends in the gender, racial, and ethnic composition of the technology sector workforce; and (2) EEOC and OFCCP oversight of technology companies’ compliance with equal employment and affirmative action requirements.

Diversity in High Tech (2016) seeks to shed more light on employment patterns in the high tech industry by providing an overview of literature as a backdrop to understanding high tech employment, and analyzing corresponding summary data from the Employer Information EEO-1 Report collected in 2014.

EEO-1 Job Classification Guide 2010 explains the Equal Employment Opportunity Commission’s definitions of jobs included in the EEO-1 categories.

The Political Behavior of Wealthy Americans: Evidence from Technology Entrepreneurs (2017) explores political views among the wealthy, and finds that that technology entrepreneurs support liberal redistributive, social, and globalistic policies but conservative regulatory policies.

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23andMe (2018)
Airbnb (2018)
Amazon (2018) (2017)
Apple (2017)
Atlassian (2018)
Blend (2018)
Chegg (2014)
Cisco (2018)
Clover Health (2018)
Dropbox (2018)
Ebay (2018)
Facebook (2018)
Google (2019)
Groupon (2017)
HP (2017)
Intel (2018)
Intuit (2018)
LinkedIn (2018)
Lyft (2018)
Modzilla (2018)
Microsoft (2018)
NetApp (2018)
NVIDIA (2015)
Pandora (2018)
Paypal (2017)
Pintrest (2018)
Salesforce (2018)
Slack (2018)
Spotify (2018)
Square (2017)
Twitter (2018)
Uber (2018)
Yahoo (2016)
Yelp (2018)

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