Category Archives: Discrimination

A Tale of Two Forums: Employment Discrimination Outcomes in Arbitration and Litigation

Source: Mark Gough, ILR Review, OnlineFirst, Published April 24, 2020
(subscription required)

From the abstract:
This article presents data from a novel survey of 1,256 employment plaintiff attorneys to test whether employee rights and remedies are affected by mandatory employment arbitration. By surveying attorneys directly about their most recent employment discrimination cases taken to verdict in arbitration and civil litigation, the author presents a systematic empirical comparison of outcomes between civil courts and arbitration with robust controls. The ability to control for the legal basis of the claim, defendant size, use of summary judgment, and attorney and plaintiff characteristics significantly improves on previous empirical research studies. Consistent with previous research, employee win rates in arbitration are lower than those found in state and federal court. In addition, monetary award amounts and percentage of claim amount awarded to employees who prevail in their cases are significantly lower in arbitration compared to outcomes in state and federal jury trials.

The Invisible Web at Work: Artificial Intelligence and Electronic Surveillance in the Workplace

Source: Richard A. Bales, Katherine V.W. Stone, Berkeley Journal of Employment and Labor Law, Vol. 41 no. 1, 2020
(subscription required)

From the abstract:
Employers and others who hire or engage workers to perform services use a dizzying array of electronic mechanisms to make personnel decisions about hiring, worker evaluation, compensation, discipline, and retention. These electronic mechanisms include electronic trackers, surveillance cameras, metabolism monitors, wearable biological measuring devices, and implantable technology. With these tools, employers can record their workers ’ every movement, listen in on their conversations, measure minute aspects of performance, and detect oppositional organizing activities. The data collected is transformed by means of artificial intelligence (AI) algorithms into a permanent electronic resume that can identify and predict an individual’s performance as well as their work ethic, personality, union proclivity, employer loyalty, and future health care costs. The electronic resume produced by AI will accompany workers from job to job as they move around the boundaryless workplace. Thus AI and electronic monitoring produce an invisible electronic web that threatens to invade worker privacy, deter unionization, enable subtle forms of employer blackballing, exacerbate employment discrimination, render unions ineffective, and obliterate the protections of the labor laws.

This article describes the many ways AI is being used in the workplace and how its use is transforming the practices of hiring, evaluating, compensating, controlling, and dismissing workers. It then focuses on five areas of law in which AI threatens to undermine worker protections: antidiscrimination law, privacy law, antitrust law, labor law, and employee representation. Finally, this article maps out an agenda for future law reform and research.

“When Do You Plan on Having a Baby?” and Other Questions Not to Ask

Source: Melissa Torres, Employee Benefit Plan Review, Vol. 74, No. 5, July-August 2020
(subscription required)

From the abstract:
Employers interviewing women of child-bearing age may be tempted to ask about plans for having a baby, but doing so poses risks. While an employer might be concerned about staffing coverage, the Pregnancy Discrimination Act prohibits employers with 15 or more employees from discriminating against a woman based on her potential or capacity to become pregnant. Taking adverse action against a pregnant employee because of her pregnancy is equally unlawful.

Nonetheless, an article in The New York Times not too long ago bore the striking headline: “Pregnancy Discrimination Is Rampant Inside America’s Biggest Companies.” The article indicated that, notwithstanding the law, many pregnant women were either passed over for promotions or fired when they complained.

Yet another Times headline focused on the failure of employers to provide light duty to pregnant women: “Miscarrying at Work: The Physical Toll of Pregnancy Discrimination.”

“Defund the (School) Police”?: Bringing Data to Key School-to-Prison Pipeline Claims

Source: Michael Heise, Jason P. Nance, Cornell Legal Studies Research Paper 20-23, August 23, 2020

From the abstract:
Calls across the nation to “Defund the Police,” largely attributable to the resurgent Black Lives Matter demonstrations, motivated derivative calls for public school districts to consider “defunding” (or, at the very least, revisit or modify) school resource officer (“SRO/police”) programs. To be sure, a school’s SRO/police presence—and the size of that presence—may influence the school’s student discipline reporting policies and practices. How schools report student discipline and whether it involves referrals to law enforcement agencies matter, particularly as it may fuel a growing “school-to-prison pipeline.” The “school-to-prison pipeline” research literature features two general claims that frame key debates about changes in how public schools approach student discipline and the growing calls to defund school resource officer programs. One is that public schools’ increasingly “legalized” approach toward student discipline increases the probability that students will be thrust into the criminal justice system. A second, distributional claim is that these adverse consequences disproportionately involve students of color, boys, students from low-income households, and other vulnerable student sub-groups. Both claims include important legal and policy dimensions as students’ adverse interactions with law enforcement agencies typically impose negative consequences on students and their futures. We subject both claims to the nation’s leading data set on public school crime and safety, supplemented by data on state-level mandatory reporting requirements and district-level per pupil spending, and explore three distinct analytic approaches in an effort to better isolate the possible independent influence of a school’s SRO/police presence on that school’s student discipline reporting behavior. Results from our analyses, largely robust to various analytical approaches, provide mixed support for the two claims. Specifically, and largely consistent with prior research, we find that a SRO/police presence at a school corresponds with an increased probability that the school will report student incidents to law enforcement agencies. However, we do not find support in the school-level data for the distributional claim.

The Relationship between Prejudice and Wage Penalties for Gay Men in the United States

Source: Ian Burn, ILR Review, Volume 73 Issue 3, May 2020
(subscription required)

From the abstract:
This article estimates the empirical relationship between prejudicial attitudes toward homosexuality and the wages of gay men in the United States. It combines data on prejudicial attitudes toward homosexuality from the General Social Survey with data on wages from the U.S. Decennial Censuses and American Community Surveys—both aggregated to the state level. The author finds that a one standard deviation increase in the share of individuals in a state who are prejudiced toward homosexuals is correlated with a decrease in the wages of gay men of between 2.7% and 4.0%. The results also suggest that the prejudice of managers is responsible for this correlation. The author finds that a one standard deviation increase in the share of the managers in a state who are prejudiced toward homosexuals is associated with a 1.9% decrease in the wages of gay men. The author finds no evidence that the wage penalty for gay men is correlated with the prejudice of customers or co-workers.

Racial Economic Inequality Amid the COVID-19 Crisis

Source: Bradley L. Hardy, Trevon D. Logan, Hamilton Project, Brookings Institution, Essay 2020-17 August 2020

From the introduction:
COVID-19 confronts Americans with two crises: a public health crisis and an economic crisis. The two operate together, since the public health crisis has dramatically reduced economic activity and overall spending. Moreover, this crisis has broader distributional consequences than any economic event in recent memory, altering most aspects of how we live, work, and conduct business—and in truth, who will survive.

Across the economy and society, the distributional consequences of COVID-19 are uneven: the pandemic and its broader economic and health consequences are disproportionately impacting Black Americans.

The outsized challenges that Black Americans are facing are a reflection of the generally diminished economic position and health status that they faced prior to this crisis. Several pre–COVID-19 economic conditions—including lower levels of income and wealth, higher unemployment, and greater levels of food and housing insecurity—leave Black families with fewer buffers to absorb economic shocks and contribute to Black households’ vulnerability to the COVID-19 economic crisis.

The interaction of those pre–COVID-19 economic and health disparities—including a higher rate of preexisting health conditions such as hypertension and lung disease—has contributed to higher COVID-19 mortality rates for Black Americans (e.g. Benitez, Courtemanche, and Yelowitz 2020; Weimers et al. 2020). According to the APM Research Lab, Black Americans continue to experience the highest overall actual COVID-19 mortality rates (80.4 per 100,000)—more than twice the rate of white Americans (35.9 per 100,000) or Asian Americans (33.1 per 100,000), who have the lowest COVID-19 mortality rates. In 2020 more Black Americans will die of COVID-19 than will succumb to diabetes, strokes, accidents, or pneumonia. In fact, COVID-19 is currently the third leading cause of death for Black Americans (APM Research Lab 2020).

The COVID-19 public health and economic crises leave vulnerable populations exposed

Source: Jevay Grooms, Alberto Ortega, and Joaquin Alfredo-Angel Rubalcaba, Brookings Institution, August 13, 2020

The coronavirus (COVID-19) pandemic has created a new reality worldwide. In the United States it has exposed the fragility of some of the most marginalized groups, particularly the millions of Americans we rely on for some of our most basic necessities. The pandemic has arguably buttressed the racial and ethnic inequities that persist in our society. Black and Hispanic households face additional social and economic disparities which are deeply rooted in structural discrimination and systemic racism—both of which have tremendous implications for health and well-being.

We use a novel panel data set collected between March and July of 2020 to describe disparities in outcomes related to the COVID-19 pandemic across race/ethnicity and employment status. Essential workers are a new class of employee defined as those who work in industries that are considered essential for a society’s survival, including (among others) health care, food service, and public transportation. We find that unemployed and essential workers are the most vulnerable given their lower income, lack of health insurance, and differences across household structure. When evaluated across race/ethnicity, the results suggest that some of these disparities are intensified among Black and Hispanic Americans.

This timely evidence suggests a need for a more robust safety net, such as an expanded unemployment benefits program and more-accessible public health insurance during the COVID-19 pandemic, as well as more-deliberate targeting of federal support to Black and Hispanic households.

Why Do Boards Have So Few Black Directors?

Source: J. Yo-Jud Cheng , Boris Groysberg and Paul M. Healy, Harvard Business Review, August 13, 2020

…The deaths of George Floyd, Breonna Taylor, Ahmaud Arbery, Rayshard Brooks, and so many other Black Americans has brought the long history of systemic racism in the United States into sharp focus over the past several months. Pressure is mounting on corporate leaders to consider how their companies can address and rectify ongoing racial injustices. So what are the factors that perpetuate the continuing underrepresentation of Black professionals on boards? And what can be done to change the systems that reinforce these disparities?…

Addressing Artificial Intelligence-Based Hiring Concerns

Source: Dave Zielinski, HR Magazine, Summer 2020

The honeymoon is over for the use of artificial intelligence in human resources. The introduction of a bevy of new artificial intelligence (AI) tools by industry vendors over the past few years was met with a buzz, and it was embraced by HR practitioners seeking to use machine-learning algorithms to bring new efficiencies to recruiting, employee engagement, shared services, learning and development, and other areas of HR.

But as the use of AI has grown, it has attracted more attention from regulators and lawmakers concerned about fairness and ethical issues tied to the technology. Chief among those concerns are a lack of transparency in the way that many AI vendors’ tools work—namely that too many still function as “black boxes” without an easily understood explanation of their inner workings—and that machine-learning algorithms can perpetuate or even exacerbate unconscious bias in hiring decisions.

Why Retirement, Social Security, and Age Discrimination Policies Need to Consider the Intersectional Experiences of Older Women

Source: Ian Burn, Patrick Button, Theodore F Figinski, Joanne Song McLaughlin, Public Policy & Aging Report, Volume 30, Issue 3, 2020
(subscription required)

From the abstract:
Population aging makes retirement security a critical issue. Unfortunately, retirement security is deteriorating over time, and there is a significant amount of income inequality in retirement (Poterba, 2014). Recent cuts to Social Security (e.g., the increase in the full retirement age [FRA], which is the age at which workers can retire with full benefits) partly drive the erosion in retirement security, and similar cuts may be forthcoming. Extending work lives into older ages is thus increasingly important to improve retirement security (Button, 2020; Maestas, 2010, 2018).

However, retirement security is significantly worse for older women, compared to older men, as older women face higher rates of poverty, especially at older ages. Figure 1 shows that poverty rates for older men are relatively consistent by age, ranging from 7.1% to 8.1%. For women, poverty rates start at 8.4% for ages 65 to 69 (compared to 7.1% for men) and rise to 13.5% for ages 80 and older (compared to 8.1% for men). This disparity in poverty rates may be increasing due to the COVID-19 pandemic and the current recession, as early evidence suggests that women ages 65 and older faced larger increases in unemployment rates compared to men and younger women (Bui, Button, & Picciotti, 2020).

In this report, we document trends and policies that contribute to the increased poverty faced by older women. We hope our examples of how older women face different experiences make a clear case for considering the impacts on older women, specifically, when setting policy.