A fairness scale for real-time recidivism forecasts using a national database of convicted offenders

Jacob Verrey, Peter Neyroud, Lawrence Sherman, Barak Ariel

Open source

DOI: 10.1007/s00521-025-11478-x
Published: 2025-08-01
Container: Neural Computing and Applications
Publisher: Springer Science and Business Media LLC
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1007/s00521-025-11478-x,
  title = {A fairness scale for real-time recidivism forecasts using a national database of convicted offenders},
  author = {Jacob Verrey and Peter Neyroud and Lawrence Sherman and Barak Ariel},
  year = {2025},
  journal = {Neural Computing and Applications},
  doi = {10.1007/s00521-025-11478-x},
  url = {https://doi.org/10.1007/s00521-025-11478-x}
}

RIS

TY  - JOUR
TI  - A fairness scale for real-time recidivism forecasts using a national database of convicted offenders
AU  - Jacob Verrey
AU  - Peter Neyroud
AU  - Lawrence Sherman
AU  - Barak Ariel
PY  - 2025
JO  - Neural Computing and Applications
DO  - 10.1007/s00521-025-11478-x
UR  - https://doi.org/10.1007/s00521-025-11478-x
ER  -

APA

Verrey, J., Neyroud, P., Sherman, L., & Ariel, B. (2025). A fairness scale for real-time recidivism forecasts using a national database of convicted offenders. Neural Computing and Applications. https://doi.org/10.1007/s00521-025-11478-x

Source records

crossref · retrieved 2026-09-26T20:48:26.090Z