Category Archives: Discrimination

Given a test to apply for a job? Watch out if you are not a white man

Source: Will Evans, Reveal, May 23, 2017

There’s a hidden form of discrimination blocking job seekers across the country.

It’s not a cabal of racist, sexist hiring managers colluding to give white men an advantage – though it can have the same effect.

It’s the misuse of employment tests – which measure reading, math and other cognitive skills – that can unfairly disadvantage minorities and women without the employers or the job applicants even realizing it…..

Symposium: Court clarifies review of racial gerrymandering, but does not impose strict scrutiny on every intentional creation of a majority-minority district

Source: Kristen Clarke and Ezra Rosenberg, SCOTUSblog, May 22, 2017

As we prepare for the upcoming round of 2020 redistricting, the opinions in Bethune-Hill v. Virginia State Board of Elections and Cooper v. Harris make clear that what constitutes unlawful racial gerrymandering will prove critical. Although states and localities can act intentionally to preserve and create majority-minority districts, they must do so in a way that complies with the Constitution. First, and put simply, race cannot predominate over every other consideration. And, second, unlawful racial gerrymandering cannot be justified as an attempt to achieve partisan ends.

The decisions provide a workable approach for addressing allegations of unconstitutional racial gerrymanders, while at the same time rejecting the proposition that the intentional creation of a majority-minority election district automatically triggers strict scrutiny. This is clear from the sum and substance of the majority opinions, and from the explicit language in the separate opinions of Justices Samuel Alito and Clarence Thomas in Bethune-Hill and that of Thomas in Cooper. A contrary result would have imperiled legitimate attempts by state legislatures to create majority-minority districts….

Equal Pay for Mothers Is Critical for Families

Source: Jasmine Tucker, National Women’s Law Center, Fact Sheet, May 2017

From the summary:
More than 22.8 million mothers with children under 18 are in the workforce, making up nearly 1 in 6 – or 15.5 percent – of all workers. The great majority of these mothers work full time. In 2015, 42 percent of mothers were sole or primary family breadwinners, while 22.4 percent of mothers were co-breadwinners, meaning families are increasingly relying on mothers’ earnings.

While women in the U.S. who work full time, year round are typically paid just 80 cents for every dollar paid to their male counterparts, the wage gap between mothers and fathers is even larger. Mothers working full time, year round outside the home are paid just 71 cents for every dollar paid to fathers, a gap that translates to a loss of $16,000 annually. The wage gap between mothers and fathers exists across education level, age, location, race, and occupation, and compromises families’ economic security….

Project Implicit

Source: Project Implicit, 2017

Project Implicit is a non-profit organization and international collaboration between researchers who are interested in implicit social cognition – thoughts and feelings outside of conscious awareness and control. The goal of the organization is to educate the public about hidden biases and to provide a “virtual laboratory” for collecting data on the Internet. ….

People don’t always say what’s on their minds. One reason is that they are unwilling. For example, someone might report smoking a pack of cigarettes per day because they are embarrassed to admit that they smoke two. Another reason is that they are unable. A smoker might truly believe that she smokes a pack a day, or might not keep track at all. The difference between being unwilling and unable is the difference between purposely hiding something from someone and unknowingly hiding something from yourself.

The Implicit Association Test (IAT) measures attitudes and beliefs that people may be unwilling or unable to report. The IAT may be especially interesting if it shows that you have an implicit attitude that you did not know about. For example, you may believe that women and men should be equally associated with science, but your automatic associations could show that you (like many others) associate men with science more than you associate women with science.

We hope you have been able to take something of value from the experience of taking one or more of these tests. The links above will provide more information about the IAT and implicit attitudes; we will periodically update the information to reflect our current understanding of the unconscious roots of thought and feeling.

When Building a Diverse Workforce, Hiring Is Just the Start

Source: Katherine Barrett & Richard Greene, Governing, May 4, 2017

Diversity has a lot of benefits, but achieving it isn’t as easy as it sounds.
Related:
Diversity at the top: The King County story
Source: Katherine Barrett & Richard Greene, May 16, 2017

Our most recent Governing column looked at growing efforts to increase diversity in the workforce. Local governments and states increasingly work to make sure that their employees mirror the population and many have been successful. But there are far fewer governments that have achieved balanced representation in the top layers of management and salary.

King County has been setting aggressive goals for that top layer. It already has a workforce that generally mirrors the community, says Matias Valenzuela, director of the office of equity and social justice. Now, its aim is to also achieve diversity in its management leadership and staff.

Why big-data analysis of police activity is inherently biased

Source: William Isaac, Andi Dixon, The Conversation, May 9, 2017

….At its core, any predictive model or algorithm is a combination of data and a statistical process that seeks to identify patterns in the numbers. This can include looking at police data in hopes of learning about crime trends or recidivism. But a useful outcome depends not only on good mathematical analysis: It also needs good data. That’s where predictive policing often falls short.

Machine-learning algorithms learn to make predictions by analyzing patterns in an initial training data set and then look for similar patterns in new data as they come in. If they learn the wrong signals from the data, the subsequent analysis will be lacking…..

Related:
Policing
Source: Human Rights Data Analysis Group, 2017

The growing debate about policing in America arises from concern about horrific but extraordinary acts of police violence. These incidents and the clear racial disparities in criminal justice contact raise important questions about the ordinary practice of policing. Should police stop suspicious individuals and frisk them for weapons? Should departments use statistical techniques to predict crime and make decisions about where to deploy officers? Evaluating police practices requires measuring their benefits and their costs. Do police practices reduce crime? How do they affect communities? How do those effects vary within and among communities? However, community groups and municipal leaders outside law enforcement currently lack data and tools to measure the impact of policing strategies. Community stakeholders – including city governments, community groups, and non-governmental organizations – need rigorous tools to independently evaluate the costs and benefits of various policing strategies.

To assess the benefits and costs of policing, we need to know how police actions affect patterns of crime. Both components – police actions and crime – are hard to measure. Most crime is secret and police practices influence variation in recording of crimes. When departments hire more officers, or when they deploy more officers to certain neighborhoods, recorded crime may increase even if actual crime does not change. Additionally, police knowledge about crime is the result of reporting by civilians who trust the police. Many victims are reluctant to report crime to police because they think the police will be unable to help them, because they worry that police may suspect them of being criminals themselves, or because they fear retaliation from perpetrators or neighbors.

Our team specializes in collecting and analyzing data on events that are hard to measure. In the last year, the Human Rights Data Analysis Group has begun studying issues in U.S. police practice, focusing on three topics: homicides by police, predictive policing, cost-benefit analysis of policing. We have already created multiple new analyses of available data on crime and policing, assessing the accuracy of the number of killings by police and the effects of Predictive Policing. We propose to build on our work to create a scalable, sustainable, community-driven, technically rigorous assessment of the costs and benefits of various policing strategies….

Lifetime Disadvantage, Discrimination and the Gendered Workforce (Chapter One)

Source: Susan Bisom-Rapp & Malcolm Sargeant, Thomas Jefferson School of Law Research Paper No. 2958253, posted May 3, 2017

Cambridge University Press, 2016

From the abstract:
Lifetime Disadvantage, Discrimination and the Gendered Workforce fills a gap in the literature on discrimination and disadvantage suffered by women at work by focusing on the inadequacies of the current law and the need for a new holistic approach. Each stage of the working life cycle for women is examined with a critical consideration of how the law attempts to address the problems that inhibit women’s labor force participation. By using their model of lifetime disadvantage, the authors show how the law adopts an incremental and disjointed approach to resolving the challenges, and argue that a more holistic orientation towards eliminating women’s discrimination and disadvantage is required before true gender equality can be achieved. Using the concept of resilience from vulnerability theory, the authors advocate a reconfigured workplace that acknowledges yet transcends gender.

The Economic Impact of Equal Pay by State

Source: Jessica Milli, Institute for Women’s Policy Research (IWPR), Fact Sheet, #C457 May 11, 2017

From the summary:
Persistent earnings inequality for working women translates into lower lifetime pay for women, less income for families, and higher rates of poverty across the United States. In each state in the country, women experience lower earnings and higher poverty rates than men. The economic impact of this persistent pay inequality is far-reaching: if women in the United States received equal pay with comparable men, poverty for working women would be reduced by half and the U.S. economy would have added $512.6 billion in wage and salary income (equivalent to 2.8 percent of 2016 GDP) to its economy. This fact sheet presents state-level data on the impact equal pay would have on poverty and each state’s economy as well as the families living in them.