The DOI matches its Crossref record; 50 of the 52 references it cites were found in a registry or an index.
An impact assessment of machine learning risk forecasts on parole board decisions and recidivism
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Assessment tools used to predict recidivism are now widespread in most jurisdictions: bail and sentencing judges (Stevenson and Doleac, 2019; Albright, 2019), parole board members (Berk, 2017), and probation officers (Kopf, 2014) use the assessment scores to determine the level of risk.”
From Prison Rehabilitation Programs: Efficiency and Targeting (2021) · cites this paper as Berk, 2017
Citations
Cites
Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538
Agresti, A. (2002) · Wiley Series in Probability and Statistics · doi:10.1002/0471249688 · Cited by 6,746
Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction
Imbens, G. W., & Rubin, D. B. (2015) · doi:10.1017/cbo9781139025751 · Cited by 4,210
Some Methods for Strengthening the Common χ 2 Tests
Cochran, W. G. (1954) · Biometrics · doi:10.2307/3001616 · Cited by 3,718 · cited 1×
“There is a χ 2 test for ordered variables introduced originally by Cochran (1954) and by Armitage (1955) and available in the R library coin .”
MethodRegression discontinuity designs: A guide to practice
Imbens, G. W., & Lemieux, T. (2007) · Journal of Econometrics · doi:10.1016/j.jeconom.2007.05.001 · Cited by 3,701
Nonparametric Statistical Methods.
Knott, M. J., Hollander, M., & Wolfe, D. A. (1974) · Journal of the Royal Statistical Society Series A (General) · doi:10.2307/2344557 · Cited by 2,687
Identification and Estimation of Treatment Effects with a Regression-Discontinuity Design
Hahn, J., Todd, P., & Klaauw, W. (2001) · Econometrica · doi:10.1111/1468-0262.00183 · Cited by 2,679
Tests for Linear Trends in Proportions and Frequencies
Armitage, P. (1955) · Biometrics · doi:10.2307/3001775 · Cited by 2,092
(2010) · Sage eBooks · doi:10.4135/9781412961288.n40 · Cited by 2,028
Regression-discontinuity analysis: An alternative to the ex post facto experiment.
Thistlethwaite, D. L., & Campbell, D. T. (1960) · Journal of Educational Psychology · doi:10.1037/h0044319 · Cited by 1,469
Research works printed but not linked: 3
- Burgess, E. M. (1928). The Working of the Indeterminate Sentence Law and the Parole System in Illinois In Bruce, A. A., Harno, A. J., Burgess, E., & Landesco, E. W. (Eds.), Factors determining success or failure on parole, (pp. 205–249). Springfield: State Board of Parole.
- Campbell, D. T., & Stanley, J. (1963). Experimental and quasi-experimental designs for research (Independence. Kentucky: Cengage Learning).
- LaVigne, N., Bieler, S., Cramer, L., Ho, H., Kotonias, C., Mayer, D., McClure, D., Pacifici, L., Parks, E., Peterson, B., & Samuels, J. (2014). Justice Reinvestment Initaitive State Assessment Report. Washington D.C.: Bureau of Justice Assistance, U.S. Department of Justice.
Cited by
Sorted by citations
Human Decisions and Machine Predictions
Kleinberg, J., Lakkaraju, H., Leskovec, J., Ludwig, J., & Mullainathan, S. (2018) · The Quarterly Journal of Economics · doi:10.1093/qje/qjx032 · Cited by 1,040
Fairness in Criminal Justice Risk Assessments: The State of the Art
Berk, R., Heidari, H., Jabbari, S., Kearns, M., & Roth, A. (2021) · Sociological Methods & Research · doi:10.1177/0049124118782533 · Cited by 988
“Ridgeway and Berk (2017) apply a similar individual approach to stochastic gradient boosting.”
BackgroundSelf-citationOn Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks
Thulasidasan, S., (NNSA), U. N. N. S. A., Chennupati, G., Bilmes, J., Tanmoy Bhattacharya, A., & Michalak, S. (2019) · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · doi:10.2172/1525811 · Cited by 437
A systematic review of artificial intelligence impact assessments
Stahl, B. C., Antoniou, J., Bhalla, N., Brooks, L., Jansen, P., Lindqvist, B., Kirichenko, A., Marchal, S., Rodrigues, R., Santiago, N., et al. (2023) · Artificial Intelligence Review · doi:10.1007/s10462-023-10420-8 · Cited by 303
Artificial Intelligence, Predictive Policing, and Risk Assessment for Law Enforcement
Berk, R. A. (2021) · Annual Review of Criminology · doi:10.1146/annurev-criminol-051520-012342 · Cited by 213
Self-citation
Metadata
- Authors
- Berk, R.
- Affiliations
- University of Pennsylvania (US)
- Corresponding author
- Berk, Richard
- ORCID
- Berk, Richard
- Venue
- Journal of Experimental Criminology
- Published
- 2017-04-08
- Volume
- 13
- Issue
- 2
- Pages
- 193-216
- ISSN
- 1572-8315 (ISSN-L)
- 1573-3750
- OpenAlex
- W2604660495
- Cited by
- 169
- References
- 52
- Citations by year
- 2026: 8 · 2025: 16 · 2024: 20 · 2023: 62 · 2022: 17 · 2021: 17 · 2020: 14 · 2019: 9 · 2018: 4 · 2017: 2
- FWCI
- 20.30
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Experimental Criminology (publishedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Criminal Justice and Corrections Analysis
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Social Sciences › Law › Artificial Intelligence in Law
- Keywords
- parole decisions, recidivism, risk assessment, randomized experiments
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
