The DOI matches its Crossref record; 83 of the 85 references it cites were found in a registry or an index.
Predictions put into practice: a quasi-experimental evaluation of Chicago’s predictive policing pilot
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“This mostly required consideration of how the same interventions and conditions could be applied consistently and uniformly within all treated and untreated groups (Ariel et al., 2019;Hunt et al., 2014;Saunders et al., 2016).”
From ‘Led by Intelligence': A Scoping Review on the Experimental Evaluation of Intelligence-Led Policing (2024) · cites this paper as Saunders et al., 2016
In the citing paper
“Predictive social network analyses were applied by Saunders et al. (2016) to identify individuals at a higher risk of gun violence.”
From ‘Led by Intelligence': A Scoping Review on the Experimental Evaluation of Intelligence-Led Policing (2024) · cites this paper as Saunders et al., 2016
In the citing paper
“Some studies employed offender subject lists to identify or predict prolific offenders and gather intelligence to target resources effectively (e.g., Groff et al., 2015;Saunders et al., 2016).”
From ‘Led by Intelligence': A Scoping Review on the Experimental Evaluation of Intelligence-Led Policing (2024) · cites this paper as Saunders et al., 2016
In the citing paper
“These messages gave strong warnings about the increased risks associated with offending or re-offending and were considered to be forms of focused and vicarious deterrence (Ariel et al., 2019;Santos & Santos, 2016;Saunders et al., 2016).”
From ‘Led by Intelligence': A Scoping Review on the Experimental Evaluation of Intelligence-Led Policing (2024) · cites this paper as Saunders et al., 2016
In the citing paper
“However, there are inherent challenges in evaluating ILP's effectiveness, as it encompasses a policing paradigm rather than a specific program or intervention, with the result that there is a dearth of evidence on its overall effectiveness (Ratcliffe, 2021;Saunders et al., 2016).”
From ‘Led by Intelligence': A Scoping Review on the Experimental Evaluation of Intelligence-Led Policing (2024) · cites this paper as Saunders et al., 2016
In the citing paper
“However, there are inherent challenges in evaluating ILP's effectiveness, as it encompasses a policing paradigm rather than a specific program or intervention, with the result that there is a dearth of evidence on its overall effectiveness (Ratcliffe, 2021;Saunders et al., 2016).”
From ‘Led by Intelligence': A Scoping Review on the Experimental Evaluation of Intelligence-Led Policing (2024) · cites this paper as Saunders et al., 2016
In the citing paper
“although we did find one study that specifically applied the 3-i model to structure the evaluation of a person-based predictive policing model (Saunders et al., 2016).”
From ‘Led by Intelligence': A Scoping Review on the Experimental Evaluation of Intelligence-Led Policing (2024) · cites this paper as Saunders et al., 2016
In the citing paper
“This mainly includes communicating deterrent messages of 'zero-tolerance' to deter potential future offenders (Ariel et al., 2019;Saunders et al., 2016).”
From ‘Led by Intelligence': A Scoping Review on the Experimental Evaluation of Intelligence-Led Policing (2024) · cites this paper as Saunders et al., 2016
In the citing paper
“In this context, Saunders et al. (2016), who conducted interviews with police officers on the use of tactical or strategic intelligence products, argued that there needs to be practical reasoning and guidance from police command staff to frontline officers on how to effectively employ intelligence in practice.”
From ‘Led by Intelligence': A Scoping Review on the Experimental Evaluation of Intelligence-Led Policing (2024) · cites this paper as Saunders et al., 2016
Citations
Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
The central role of the propensity score in observational studies for causal effects
ROSENBAUM, P. R., & RUBIN, D. B. (1983) · Biometrika · doi:10.1093/biomet/70.1.41 · Cited by 31,241
Robust Regression: Asymptotics, Conjectures and Monte Carlo
Huber, P. J. (1973) · The Annals of Statistics · doi:10.1214/aos/1176342503 · Cited by 2,337
Serious and Violent Juvenile Offenders: Risk Factors and Successful Interventions
Janson, C.-G., Loeber, R., & Farrington, D. P. (1999) · Contemporary Sociology A Journal of Reviews · doi:10.2307/2655346 · Cited by 1,893
Cornish, D. B., & Clarke, R. V. (2014) · Cited by 1,781
Nobel Lecture: The Economic Way of Looking at Behavior
Becker, G. S. (1993) · Journal of Political Economy · doi:10.1086/261880 · Cited by 1,619
Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data
Zikopoulos, P., & Eaton, C. (2011) · Cited by 1,482
Grove, W. M., & Meehl, P. E. (1996) · Psychology, Public Policy, and Law · doi:10.1037/1076-8971.2.2.293 · Cited by 1,457
Criminal Careers and "Career Criminals,"
National Research Council (1986) · National Academies Press eBooks · doi:10.17226/922 · Cited by 1,352
McCaffrey, D. F., Ridgeway, G., & Morral, A. R. (2004) · Psychological Methods · doi:10.1037/1082-989x.9.4.403 · Cited by 1,317
Research works printed but not linked: 6
- Beck, C., & McCue, C. (2009). Predictive policing: what can we learn from Wal-Mart and Amazon about fighting crime in a recession? Police Chief, 76(11), 18.
- Eck, J., Chainey, S., Cameron, J., & Wilson, R. (2005). Mapping crime: Understanding hotspots (Vol. NCJ 209393). Washington, DC: National Institute of Justice.
- Groff, E. R., & La Vigne, N. G. (2002). Forecasting the future of predictive crime mapping. Crime Prevention Studies, 13, 29–58.
- Papachristos, A., Braga, A., & Hureau, D. (2011). Six-degrees of violent victimization: Social networks and the risk of gunshot injury. · DOI
- Pate, T., Bowers, R. A., & Parks, R. (1976). Three approaches to criminal apprehension in Kansas City: An evaluation report. Washington, DC: Police Foundation.
- Sherman, L. W., Gottfredson, D., MacKenzie, D., Eck, J., Reuter, P., & Bushway, S. (1997). Preventing crime: What works, what doesn’t, what’s promising: A report to the United States Congress. Washington, DC: US Department of Justice, Office of Justice Programs.
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Metadata
- Authors
- Saunders, J., Hunt, P., & Hollywood, J. S.
- Affiliations
- RAND Corporation (US)
- Corresponding author
- Saunders, Jessica
- Venue
- Journal of Experimental Criminology
- Published
- 2016-08-12
- Volume
- 12
- Issue
- 3
- Pages
- 347-371
- ISSN
- 1572-8315 (ISSN-L)
- 1573-3750
- OpenAlex
- W2509791345
- Cited by
- 193
- References
- 85
- Citations by year
- 2026: 15 · 2025: 14 · 2024: 12 · 2023: 17 · 2022: 30 · 2021: 24 · 2020: 28 · 2019: 26 · 2018: 15 · 2017: 10 · 2016: 2
- FWCI
- 20.27
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Experimental Criminology (publishedVersion)
- Funders
- National Institute of Justice (US) (2009-IJ-CX-K114)
- Topics
- Social Sciences › Health › Gun Ownership and Violence Research
- Social Sciences › Political Science and International Relations › Policing Practices and Perceptions
- Social Sciences › Sociology and Political Science › Crime Patterns and Interventions
- Keywords
- predictive policing, gun violence, homicide, Chicago Police Department, Compstat, arrest rates, homicide prevention, police intervention
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 ›
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