Constructing Recidivism Risk

By Jessica M. Eaglin. 2016

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Fairness and Abstraction in Sociotechnical Systems (2019, background): “These rationales are always in tension; a potential consequence of risk assessments is privileging the social value that is quantified [21].”
Algorithms, Platforms, and Ethnic Bias: An Integrative Essay Forthcoming in Phylon: The Clark Atlanta University Review of Race and Culture (2018, unknown): “Each company’s software is the product of different data sources and measurements, thus leading to discrepancies in measurement validity and different degrees of bias (Christin, Rosenblatt, & Boyd, 2015; Eaglin, 2017; Lum & Issac, 2016).”
This Thing Called Fairness (2019, background): “” [32] As we have detailed above, and others have recognized, designing algorithmic tools that align with notions of fairness and justice is complicated [33, 40, 115].”