ON AMBIGUITY IN PERCEPTIONS OF RISK:IMPLICATIONS FOR CRIMINAL DECISION MAKING AND DETERRENCE*
By Thomas A. Loughran, Raymond Paternoster, Alex R. Piquero, Greg Pogarsky. 2011
139 citations recorded by the source corpus.
Subfields: General Decision Sciences, Sociology and Political Science
View Paper: https://www.semanticscholar.org/paper/12d97d7c52a2966d9b9dab9849279f2a734388e2
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In General Decision Sciences
In Sociology and Political Science
- Hau Chan
- Milind Tambe
- Sungyong Seo
- Phebe Vayanos
- George O. Mohler
- P. Jeffrey Brantingham
- Yan Liu
- Jorja Leap
Citations in the corpus
- Partially Generative Neural Networks for Gang Crime Classification with Partial Information (2018, background): “It is no surprise, therefore, that law enforcement agencies are interested in reducing crimes by leveraging crime prediction models [7, 17] and intervention strategies optimized for deterrence [15, 18].”
- Does Predictive Policing Lead to Biased Arrests? Results From a Randomized Controlled Trial (2018, background): “The prevailing view, derived from experiments in hot spot policing (Sherman and Eck 2002; Braga and Bond 2008), is that the presence of police in a given place removes opportunities for crime even without any direct contact with potential offenders (Sherman and Weisburd 1995; Weisburd 2008; Loughran”