RT Article
T1 Overcoming the benchmark problem in estimating bias in traffic enforcement: the use of automatic traffic enforcement cameras
JF Journal of experimental criminology
VO 17
IS 2
SP 217
OP 237
A1 Factor, Roni
A2 Kaplan-Harel, Gal
A2 Turgeman, Rivka
A2 Perry, Simon
LA English
YR 2021
UL https://krimdok.uni-tuebingen.de/Record/1758377534
AB Objectives The existence of bias in law enforcement can be difficult to verify or disprove, in part because of the difficulty of finding a benchmark—an objective estimate of actual offenses committed by the studied population—that can be compared with police enforcement. In the current study, we propose and test a method for examining bias in enforcement of speeding offenses. Method Using all speeding tickets issued in Israel in 2013–2015, we compare speeding tickets generated by stationary automatic traffic cameras, which provide an objective estimate of speed offenses, with speeding tickets issued manually by police officers, based on drivers’ ethnicity with further distribution by gender and age. Results Initial findings indicate that, overall, speeding tickets issued by police officers in Israel are not biased based on drivers’ ethnicity. Conclusions This study highlights the importance of distinguishing between overrepresentation and bias in law enforcement, which sometimes seem to be blurred in the literature.
K1 Enforcement bias
K1 Policing
K1 Ethnic and racial minorities
K1 Traffic violations
K1 Speeding offenses
K1 Automatic traffic cameras
K1 Road policing
DO 10.1007/s11292-020-09414-1