The Editorial Board, Unemployment in Black and White, Washington Post, August 28, 2017. [“The hard truth is that the persistence of twice-as-high joblessness for black workers has led policy makers to accept it as normal.”]
Posted in Economic Mobility, Economics, Education, Employment, Family, Inequality, Jobs, Measuring Poverty, Op-Ed, Politics, Race, Uncategorized, Unsolicited Advice
Tracy Jan, The biggest beneficiaries of the government safety net: Working-class whites, Washington Post, February 16, 2017. [Commentary on the true effect of the government assistance and tax credit programs of 2014.]
Posted in Books, Economic Mobility, Economics, Inequality, Measuring Poverty, Politics, Race, Socio-Economic Rights, Uncategorized, War on Poverty, Welfare
James Lartey, Two schools in Mississippi – and a lesson in race and inequality in America, The Guardian Aug. 27, 2017. [A telling tale of divergent experiences in Mississippi public schools.]
New Pathways : “State of the Union 2017” (Stanford Center on Poverty and Inequality 2017). Table of contents below:
Are our country’s policies for reducing racial and ethnic inequalities getting the job done? The simple answer: No.
Even after the recovery, 1 in 9 African Americans and 1 in 6 Hispanics fear a job loss within one year. Why?
We remain two Americas: a high-poverty America for blacks, Hispanics, and Native Americans, and a (relatively) low-poverty America for whites and Asians.
The safety net, which is supposed to serve an equalizing function, sometimes works to exacerbate racial and ethnic inequalities within the low-income population.
Whereas 1 in 6 black and Hispanic households dedicate at least half of their income to housing costs, only 1 in 12 white households do. How did that happen?
Between 1990 and 2015, average academic performance improved for students of all racial and ethnic groups, but grew fastest among black and Hispanic students. The result: White-black and white-Hispanic achievement gaps declined by 15 to 25 percent.
Did you think that all that talk about criminal justice reform has brought about a sea change in racial inequalities in incarceration? Think again.
Large and persistent racial gaps in health are not the product of our genes but the consequences of our policies and history.
Between 1970 and 2010, the earnings gap between whites and other groups has narrowed, but most of that decline was secured in the immediate aftermath of the Civil Rights Movement.
African-Americans have less than 8 cents and Hispanics less than 10 cents of wealth for every dollar amassed by whites.
The persistence of poverty has long been stronger for blacks than whites. However, beginning with generations that came of age in the mid-1960s, the white-black gap in the chance of escaping poverty has closed significantly.
Confronting Poverty: Poverty Risk Calculator worth checking out and perhaps sharing with students.
Article: Mary Madden, et al., Privacy, Poverty and Big Data: A Matrix of Vulnerabilities for Poor Americans, Washington L. Rev. (forthcoming 2017).
This Article examines the matrix of vulnerabilities that low-income people face as a result of the collection and aggregation of big data and the application of predictive analytics. On the one hand, big data systems could reverse growing economic inequality by expanding access to opportunities for low-income people. On the other hand, big data could widen economic gaps by making it possible to prey on low-income people or to exclude them from opportunities due to biases that get entrenched in algorithmic decision-making tools. New kinds of “networked privacy” harms, in which users are simultaneously held liable for their own behavior and the actions of those in their networks, may have particularly negative impacts on the poor. This Article reports on original empirical findings from a large, nationally-representative telephone survey with an oversample of low-income American adults and highlights how these patterns make particular groups of low-status internet users uniquely vulnerable to various forms of surveillance and networked privacy-related problems. In particular, a greater reliance on mobile connectivity, combined with lower usage of privacy-enhancing strategies may contribute to various privacy and security-related harms. The article then discusses three scenarios in which big data – including data gathered from social media inputs – is being aggregated to make predictions about individual behavior: employment screening, access to higher education, and predictive policing. Analysis of the legal frameworks surrounding these case studies reveals a lack of legal protections to counter digital discrimination against low-income people. In light of these legal gaps, the Article assesses leading proposals for enhancing digital privacy through the lens of class vulnerability, including comprehensive consumer privacy legislation, digital literacy, notice and choice regimes, and due process approaches. As policymakers consider reforms, the article urges greater attention to impacts on low-income persons and communities.