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Brown: Evidence indicates increasing minimum wage has a modest negative impact on employment in the short term

Wagner and Heeringa study facets of suicide risk among US Army soldiers

Shaefer on study showing US spends less on poorest children, more on the elderly, than it did 20 years ago

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Call for Papers: PSID User Conference 2018: Child Wellbeing and Outcomes in Childhood, Young Adulthood, and over the Lifecourse

Martha Bailey elected to the board of the Society of Labor Economists

Patrick Kline wins SOLE's Sherwin Rosen Prize for "Outstanding Contributions in the Field of Labor Economics"

Charlie Brown elected to the board of the Society of Labor Economists

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More PSC brown bags, Fall 2018

Sonja B. Starr

Starr critical of risk assessment scores for sentencing

a PSC In The News reference, 2016

"This Guy Trains Computers to Find Future Criminals" - Bloomberg. 07/18/2016.

Some courts use automatically generated risk scores in sentencing and paroling criminals. Generated by algorithms using factors such as prior arrests, types of crimes, and demographic information, risk scores are intended to help judges overcome unconscious bias. But critics like Sonja Starr think they can hide prejudices beneath a façade of computerized objectivity. Starr says that although social science research uses socioeconomic and demographic variables to predict population-level behaviors, these models should not be used to calculate a single person’s future, especially if the variables used are influenced by decades of racial and socioeconomic disparities. It amounts to a computerized version of racial profiling. Starr says she and others are particularly concerned that "every mark of poverty serves as a risk factor" in these assessments.

Researcher:

Sonja B. Starr

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