Experiments and Data Analysis for Criminal Justice Organizations
July 14, 2020
Experiments and XXXX Analysis for Criminal Justice Organizations
X predictive XXXXXXXX model XXX used at the Shreveport Police Department to XXXXXXXX XXX likelihood of a crime occurring XXXXXX property XXXXX-XXXX XXXXX against the hot spot XXXXXXXX XXXXXXXX. The XXXXXXXX XXXXXXXXX used XXXXXXXXXX information XXXXXXX (XXX) with advanced data analytics. XXXX XX XXXXX XXXX identify hot XXXXX in geographic XXXXXXXXX XXXXX technology where XXXXXX XXX highly concentrated (XXXX, 2014). XXXX strategy XXX XXXXXXXXX at helping the police XXXXXXXXXX put XXXXX XXXXXX resources to better XXX. XXXXXX models can XXXXXXXX XXXXX the XXXXX occurs and XXX XXXXXXXXXXXX, witnesses and victims. XXX these XXXXXXXX are termed as predictive XXXXXXXX. XXX XXXXXX City XXXXXXXXXX XXXXXX XXXXXXXXXX XXXXXXXX a XXXXXXXX XXXXXXXXXX to test the XXXXXXX of police patrolling on crime. This XXXXXXXXXX XXXXXX XXXXXXXXXX XXX XXXXXXXXX by the fact that the routine patrol of XXXXXX in marked cars did not XXXX to affect the level of XXXXX in any XXX (Kelling, 2015). The plan XXX XX manipulate XXXXXX XXXXXXXXX XXXXXXX putting public XXXXXX at risk.
The XXXXXXXXXX XXXXXXXX XXXXXXXXXX XXXX at XXX Shreveport XXXXXX department share XXXX similarities with XXX preventive patrol experiments used XX the XXXXXX XXXX Police XXXXXXXXXX. Both XXXXXXXXXXX were XXXXXXXX to XXXX XX a change XX strategy XX police strategies in fighting crime would XXXXXX the XXXXX rate in the XXXXX under XXXXX. XXX XXXXXXXXXX policing targets XX XXXXXX from identifying crime XXX spots to predicting XXXX XXX who will XX XXXXXXXXXX XXX crime, or XX XXX XXXXXX. XXX XXXXXXXXXX patrols XXXX XXXXXXXX XX XXXXXX crime XXXXX XX making police XXXXXX cars more XXXXXXX to the XXXXXX XXXXXXXX so that XXXXXXXXX would XXX trace XXXXX patrol patterns (Hunt, XXXX). XX both experiments, precautions XXXX XXXXX to ensure that the experiments would XXX jeopardize the safety XX XXX XXXXXX. By XXX end XX both experiments, there XXX no significant evidence XX XXXXX XXXXXXXXX XXXX the predictive policing or XXX XXXXXXXXXX patrol experiments.
The XXX experiments XXX XXXXX XXXXXXXXXXX XXXXXXX XX XXX XXXXX XXXXXXXXXX. XXX predictive policing experiment XXX aimed XX XXXXXXXXXXX the XXXXX future property crime XXXXXXXXX. XXXX XXXXX it XXX XXXXXXXX XX XXXX XXX Shreveport XXXXXX Department respond XXXXXX to crime XXXXXX XXX XXXX XXXXXX keep an eye on XXXXX XXXX-crime XXXXXXXXXXXXX (NIJ, 2018). XXX XXXXXXXXXX XXXXXX experiment XXX designed XX scare XXXXXXXXX XXXX XXXXXXXXXX XXXXXX by increasing XXX presence XX patrol cars in XXXX XXXXX XXXXXXXXXXXXX. This one XX a XXXXXXXXXX XXXXXXX, XXXXX XX different XXXX XXX predictive XXXXXXXX designed XX XXXX the police XXXXXXX XXXXXX XX crime alerts.
The predictive policing model had XXXXXXXXXXXXXXX XXXX made it a high-XXXX XXXXXXXX XX XXX in solving XXXXXXXX XXXXX XXXXX XXXXX XXX at XXXXX. XXXX levels of ethics, like XXXXXXXX, XXX XX XX XXXXXXXXX by all agencies to help researchers collect the XXXXXXX information XXXX the XXXXX (NIJ, XXXX). Failure to observe XXX or all guidelines XX agencies involved XXXXX XXXX it hard for researchers to know XX there were changes or no XXXXXXX XXXXXXXX from the program. The XXXXXXXXXX patrol XXXXXXXXXX was XXXXXXXX XX the XXXXXXXX XX XXX XXXXXX XXXXXXXX in XXXXXX XXXXXXX they XXXXXX to wait and respond XX calls XXX service XXXXXX and non-XXXXXX related XXXXXXXXXX instead of being on XXXXXX XX XXXXXXXX (XXXXXX, 2015).
XXXXX are alternative methods XXXX could be XXXXXXX to avoid such failure of such life-XXXXXXXX in the future. The XXXXXXXXXX XXXXXXXX XXXXXXXXXX XXXXX XX improved XX improving XXXXXXXX to XXXXXXX XXX XXXXXXXX XX all agencies involved (XXXX, XXXX). XXX XXXXXXXXXX between the forecast maps XXX XXX XXX spots XXXX be XXXXXX to XXXX out the practical differences that XXXXX when it comes XX XXXXXXX’s XXXXXX. The XXXXXXXXXX patrol experiment XXXXX be XXXXXXXX XX XXXXXXXX XXXX XXXXXX go on patrol and XXX tracked XXXXX GPS, so they XXX’t XXXXXX XX XXX-XXXXXXXX XXXXXXXXXX (Larson, 2015). XXX goal of XXXX XXXXXXXXXX XXXXX XX used XXX targeted XXXXX prevention XXXXXXX of routine XXXXXXXXXX control.
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Hunt, X., XXXXXXXX, X., &XXX; XXXXXXXXX, J. S. (XXXX). XXXXXXXXXX XX XXX Shreveport XXXXXXXXXX XXXXXXXX experiment. Rand Corporation.
Kelling, G. X., XXXX, T., Dieckman, X., &XXX; XXXXX, X. E. (XXXX). XXX XXXXXX XXXX XXXXXXXXXX patrol experiment. Washington, XX: XXXXXX Foundation.
Larson, R. C. (2015). XXXX XXXXXXXX XX patrol XXXXXXXXXX in Kansas XXXX? A XXXXXX XX XXX XXXXXX XXXX XXXXXXXXXX patrol XXXXXXXXXX. Journal of criminal justice, 3(X), 267-297.
National Institute of XXXXXXX (XXX), US XXXXXXXXXX of Justice, Office XX XXXXXXX XXXXXXXX, & XXXXXX XXXXXX XX XXXXXXX. (2018). Evaluation XX XXX Shreveport Predictive XXXXXXXX XXXXXXXXXX, web XXXXXXX.