Source: Alex Press, Vox, May 9, 2019
…. Numbers released by the Equal Employment Opportunity Commission (EEOC), the federal agency responsible for enforcing civil rights laws against gender, race, religious, and other forms of workplace discrimination, show that even as the overall number of complaints received is down 9.3 percent from 2017, complaints about sexual harassment rose 13.6 percent over the previous year. ….
Source: Patrick Dixon, Labor: Studies in Working-Class History of the Americas, Vol. 16 no. 2, May 2019
From the abstract:
The results of the 2016 election presented a crisis for American progressives that has given birth to a new genre of popular nonfiction literature focused on resistance to the Trump administration. These primers seldom consider labor to be an important element of resistance, and while they include many policy prescriptions, these are often lacking in imagination and ambition. This genre is nonetheless an instructive source, offering a historical snapshot that reveals the fissures and dilemmas facing the American Left in the early days of the Trump presidency.
Source: Timothy Reese Cain, Philip J. Wilkinson, Labor: Studies in Working-Class History of the Americas, Vol. 16 no. 2, May 2019
From the abstract:
Through a historical case study of the University of Wisconsin Teachers Union (American Federation of Teachers Local 223) this article considers the roles that early unionized faculty could play in influencing their institution without ever pursuing a contract. It argues that the Wisconsin local effectively used research and political power to improve conditions for instructional workers and to affect funding patterns across the institution. It did so while only ever attracting a minority of faculty to join. In addition to its important salary work, which was often focused on improving the conditions of the instructors and others at the lowest ranks, Local 223 addressed an array of educational and societal issues. As such, it had elements of what in the modern era might be considered social movement unionism, combining both efforts to aid members and activities designed for broader social change.
Source: Lane Windham, Labor: Studies in Working-Class History of the Americas, Vol. 16 no. 2, May 2019
From the abstract:
Anyone who glimpsed the diverse group of young women intently conferencing at Georgetown University might have mistaken them for diligent students. In fact, they were the inaugural apprenticeship class of the WILL Empower initiative that is designed to identify, nurture, and train a new generation of women labor leaders. The Apprenticeship Program is one of four interwoven programs spearheaded by WILL Empower (Women Innovating Labor Leadership), jointly founded in 2017 by Georgetown University’s Kalmanovitz Initiative for Labor and the Working Poor and Rutgers University’s Center for Innovation in Worker Organization. By focusing on building women’s leadership for a broad range of worker-based economic justice organizations, WILL Empower is breaking fresh ground even as the nation’s political economy remains stubbornly stacked against working people.
Three big ideas undergird WILL Empower’s unique approach to building a successful twenty-first-century labor movement: (1) women must lead at a whole new level, especially women of color; (2) traditional labor unions and new forms of worker organizations constitute a single movement; (3) a multilayered partnership can model the sort of innovative approach that the movement needs……
Source: Congressional Research Service, CRS Insight, IN11098, April 11, 2019
Economists and financial markets closely monitor interest rates in hopes of gleaning information about the path of the economy. One measure of particular interest is the “yield curve.” Recently, the yield curve associated with U.S. Treasuries inverted. This Insight discusses possible explanations for the inversion, including whether the inversion is signaling that the economy will enter a recession.
Source: Lisa N. Sacco, Congressional Research Service, CRS Report, R45410, April 23, 2019
The Violence Against Women Act (VAWA) was originally enacted in 1994 (P.L. 103-322). It addressed congressional concerns about violent crime, and violence against women in particular, in several ways. Among other things, it allowed for enhanced sentencing of repeat federal sex offenders; mandated restitution to victims of specified federal sex offenses; and authorized grants to state, local, and tribal law enforcement entities to investigate and prosecute violent crimes against women.
This report provides a brief history of VAWA and an overview of the crimes addressed through the act. It includes brief descriptions of earlier VAWA reauthorizations and a more-detailed description of the most recent reauthorization in 2013. It also briefly addresses reauthorization activity in the 116th Congress. The report concludes with a discussion of VAWA programs and a five-year history of funding from FY2015 through FY2019.
Source: GAO-19-257, Published: March 7, 2019
From the summary:
Robots, artificial intelligence, and other advanced technologies are changing the workplace. We visited companies to observe the effects on workers. Effects varied, with some companies reducing their workforces, many moving workers to different roles, and some hiring workers due to increased production or new skill needs.
Workforce data doesn’t identify the causes of employment shifts, making it difficult to assess technology’s effects. Additional information could help agencies design programs to prepare workers for jobs of the future.
We recommended that the Department of Labor develop ways to better track workforce effects of technologies…..
Source: Jason R. Bent, Georgetown Law Journal, Forthcoming, Date Written: April 16, 2019
From the abstract:
It is now understood that machine learning algorithms can produce unintentionally biased results. For the last few years, legal scholars have been debating whether the disparate treatment or disparate impact theories available under Title VII of the Civil Rights Act are capable of protecting against algorithmic discrimination. But machine learning scholars are not waiting for the legal answer. Instead, they have been working to develop a wide variety of technological “fairness” solutions that can be used to constrain machine learning algorithms. They have discovered that simply blinding algorithms to protected characteristics like sex or race is insufficient to prevent algorithmic discrimination. Given enough data, algorithms will identify and leverage on proxies for the protected characteristics. Recognizing this, some scholars have proposed “fairness through awareness” or “algorithmic affirmative action” — actively using sensitive variables like race or sex to counteract unidentified sources of bias and achieve some mathematical measure of fairness in algorithmic decisions. But is algorithmic affirmative action legal? This article is the first to comprehensively consider that question under both Title VII and the Equal Protection clause of the Fourteenth Amendment. The article evaluates the legality of the leading fairness techniques advanced in the machine learning literature, including group fairness, individual fairness, and counterfactual fairness. The article concludes that existing affirmative action doctrine under Title VII and existing constitutional equal protection jurisprudence leave sufficient room for at least some forms of algorithmic affirmative action.
Source: Daniel Kuehn, Economic Development Quarterly, OnlineFirst, Published March 29, 2019
From the abstract:
Registered apprenticeship is a time-tested approach to building technical skills through a combination of classroom and closely supervised on-the-job training. This study explores the growth of registered apprenticeship in service occupations over the past two decades and uses administrative data on registered apprentices to identify the factors associated with successful program completion and exit wage growth. Key program characteristics vary across different service occupations, but shorter apprenticeship programs operated by single employers working jointly with a union seem to be consistently associated with higher completion rates. Partnerships with community colleges fail to generate higher completion rates, although for many service occupations these partnerships are associated with higher exit wages.
Source: Hanadi Hamadi, Janice C. Probst, M. Mahmud Khan, Aurora Tafili, Home Health Care Management & Practice, OnlineFirst, Published April 13, 2019
From the abstract:
The purpose of this study was to describe personal, job, agency, environmental, and ergonomic factors that affect job satisfaction among home health workers (HHWs). A cross-sectional design was conducted, and data from the National Home and Hospice Care Survey (N = 3,274) were analyzed using a multilevel structural equation model (generalized structural equation model). HHWs with excellent training knowledge were about 1.5 times more likely to report a higher degree of job satisfaction compared with those with poor training knowledge, and those who reported a work-related injury were 66% more likely to report lower job satisfaction score. Job satisfaction is associated with work environment, leadership support, and work-related training. Future research and a follow-up survey are needed to understand HHWs’ workforce and be better positioned to meet their need so that they may meet the need of the aging population.