Actuarial Sentencing: An “Unsettled” Proposition

By Kelly Hannah-Moffat. 2013

130 citations recorded by the source corpus.

Subfields: Clinical Psychology, Sociology and Political Science

How researchers see this paper

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

In Clinical Psychology

1. S. Prins
2. Jiaming Zeng
3. Berk Ustun
4. Momin M. Malik
5. Cynthia Rudin
6. A. Reich

In Sociology and Political Science

1. S. Prins
2. Jiaming Zeng
3. Berk Ustun
4. Momin M. Malik
5. Cynthia Rudin
6. A. Reich

Citations in the corpus

• Interpretable classification models for recidivism prediction (2015, methodology): “Many tools use the risk estimate to produce several outcomes (e.g.,“low risk,” “medium risk” and “high risk) with thresholds that are decided arbitrarily (Hannah-Moffat 2013).”
• A Hierarchy of Limitations in Machine Learning (2020, methodology): “This approach, though, was gradually replaced by one based on optimization and correlation that was far more empirically successful, just as in risk assessment at the same time (Hannah-Moffat, 2013).”
• Can we avoid reductionism in risk reduction? (2017, background): “, 2008), and legal and correctional professionals frequently do not understand the actuarial technologies upon which they base their decisions (Hannah-Moffat, 2012).”