Diversity Reports

Race, States, and the Mixed Fate of White Men

January, 2019
by
Donald Tomaskovic-Devey & Eric Hoyt

A great deal of media attention has been placed on the perceived threat to White male employment. Has the entrance of more women and minority men into the labor market made it harder for White men to secure jobs, or has this competition helped push White men into more desirable jobs? Using data collected by the U.S. Equal Employment Opportunity Commission (EEOC) from private sector firms with more than 100 employees (50 if federal contractors), our analysis explores employment diversity in these workplaces to better understand for where competition is greatest. The general pattern shows that educated White men are strongly advantaged in their access to upper class jobs in states with large minority populations, while those with less education face increased labor market competition for working class positions. 

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Is Silicon Valley Tech Diversity Possible Now?

January, 2018
by
Donald Tomaskovic-Devey & Joo-Hee Han

In this report, we ask a set of new questions: Are all of the largest firms in the Northern California Tech sector consistently tilted toward white men? Or, as we suspect, is there important firm variation in the ability to recruit and retain a more diverse workforce? Are there firms that demonstrate that diversity is currently possible in Silicon Valley?  In this report we show that some firms have figured out how to thrive with racially and gender diverse workforces, so now the question becomes why some don't ?

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Count and Compare: One Strategy for Reducing Discrimination

January, 2018
by
Donald Tomaskovic-Devey

There is now a consensus that accountability and transparency are necessary to reduce bias and increase diversity in employment. Neither is possible, in the absence of metrics. Imagine pay for performance with no performance metric? How about a stock analyst with no performance data? We must count diversity, disparity and dignity. Once the metrics are in place, accountability and transparency are possible. Without them it’s only shadowboxing in the dark.

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Employer’s Responses to Sexual Harassment

January, 2018
by
Carly McCann, Donald Tomaskovic-Devey, and M. V. Lee Badgett

#MeToo, #TimesUp, and related movements have brought renewed attention to workplace sexual harassment. However in everyday workplaces, the vast majority of allegations go unreported, and those that do report tend to face troubling outcomes.

Our research, recently released by the University of Massachusetts-Amherst’s Center for Employment Equity, analyzed all sexual harassment complaints filed with the U.S Equal Employment Opportunity Commission (EEOC) and state Fair Employment Practices Agencies (FEPA) between 2012-2016. We find that nearly all sexual harassment goes unreported, but those that do report tend to face severe retribution and limited redress.

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Who’s Getting the Skilled Blue Collar Jobs? A Look into the Top and Bottom 5 States

January, 2018
by
Eric Hoyt & J.D. Swerzenski

Surveying press coverage around blue collar employment over the past several years, it’s often been the case that “blue collar” has in fact acted shorthand for  white working class menOur focus in this report is to expand the conversation by examining the racial employment diversity among skilled craft and trade workers, a slice of the blue collar labor market including carpenters, mechanics, plumbers, and more. So who actually is getting these high-paying blue-collar jobs, and to what degree does the press narrative around blue collar employment hold up? Our analysis reveals that the craft workforce is racially diverse and geographically varied, but overwhelmingly male-dominated.

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Here’s the clearest picture of Silicon Valley’s diversity yet: It’s bad. But some companies are doing less bad

January, 2018
by
By Sinduja Rangarajan

This report was published by Reveal: The Center for Investigative Reporting in collaboration with the Center for Employment Equity. 

Ten large technology companies in Silicon Valley did not employ a single black woman in 2016. Three had no black employees at all. Six did not have a single female executive. In stark contrast, women outnumbered men in the executive ranks of two Silicon Valley companies, and at another firm, nearly a third of executives were women of color. A first-of-its kind analysis of 177 of the largest San Francisco Bay Area tech firms by Reveal from The Center for Investigative Reporting found that while racial and gender disparities are grave, many companies haven’t been held back by conventional excuses.

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New Evidence from the Frontlines on Sexual Orientation and Gender Identity Discrimination

January, 2017
by
M. V. Lee Badgett, Amanda Baumle, and Steven Boutcher

In this report, we analyze data on the 9,121 SOGI discrimination charges filed with the EEOC or with a state or local fair employment practices agency (FEPA) between 2013 and 2016. These charges provide an unprecedented view into the situations where employees believe that they have faced discrimination because of their sexual orientation and/or gender identity. We report on trends in charge filing over time and on patterns by industry, issues raised and outcomes of the charges. 

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Employment Patterns in the Oil & Gas Industries

January, 2016
by
Donald Tomaskovic-Devey

There are three industries central to the production and distribution of oil and gas in the United States. Oil and Gas Extraction is a mining industry. Petroleum and Coal Manufacturers convert both energy sources to usable fuels. Gas pipelines is a transportation industry delivering oil and natural gas from production sites to consumption. The latter is not exhaustive as some transportation is also done by rail and truck, although these cannot be identified separately.

In this report we use information from EEO-1 reports and from the American Community Survey to assess the degree of employment equity in these three oil and gas related industries. The EEO- 1 reports describe workplace level employment composition and are submitted to the U.S. Equal Employment Opportunity Commission by private sector employers with 100 or more employees, 50 or more if government contractors. The American Community Survey is collected by the U.S. Bureau of the Census and is used to describe the U.S. population. 

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Private Sector Industry Disparities: A Report on Evidence of Systemic Disparities for Women, African Americans, Hispanics, Asians and Native Americans

January, 2012
by
Donald Tomaskovic-Devey, Karen Brummond, JooHee Han, Skylar Davidson

Prepared for the U.S. Equal Employment Opportunity Commission We grade U.S. private sector industries based on 2012 group employment disparities. The EEOC primarily responds to discrimination complaints from citizens. When evaluating these complaints investigators often refer to EEO-1 data on workplace employment distributions compared to the available labor force to develop an estimate of employment disparity. Using the same logic, we produce industry estimates of employment disparities. The report may be useful in a number of ways. It is possible for the EEOC to issue Commissioner’s charges when systemic bias is suspected. This report identifies industries that might be considered for Commissioner’s charges. The OFCCP currently selects firms for random audits of their employment practices.

This report provides additional information useful for more targeted enforcement. Finally, the report could be useful if regulatory authorities wanted to identify industries with particularly good records to single out for public praise. We employ 2012 EEO-1 private sector reports of annual reporting establishment workforce composition to produce industry level employment disparity and segregation estimates. This is a preliminary report and we look for ways to tailor the report more closely to the needs of the regulatory, employee, and business communities. We focus on four types of workplace disparity: overall employment representation, managerial representation , occupational segregation, and wage gaps. We describe industry variation in these employment outcomes for women, African Americans, Hispanics, Asians, and Native Americans. We use 2007-2011 American Community Survey (ACS) Public Use Microdata Samples (PUMS) to compute a set of expected employment baselines and to estimate industry level wage disparities. Wage gap results are computed from the 2007-2011 American Community Survey (ACS) Public Use Microdata Samples (PUMS). We limited the 2012 EEO-1 data to single establishment employer reports, multiple establishment firms’ individual establishment reports, and multiple establishment firms’ headquarters reports. We examined data only for establishments with at least 50 employees.

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