Increasing Cooperation With the Police Using Body Worn Cameras

What can change the willingness of people to report crimes? A 6-month study in Denver investigated whether Body Worn Cameras (BWCs) can change crime-reporting behavior, with treatment-officers wearing BWCs patrolling targeted street segments, while control officers patrolled the no-treatment areas without BWCs. Stratified street segments crime densities were used as the units of analysis, in order to measure the effect on the number of emergency calls in target versus control street segments. Repeated measures ANOVAs and subgroup analyses suggest that BWCs lead to greater willingness to report crimes to the police in low crime density level residential street segments, but no discernable differences emerge in hotspot street segments. Variations in reporting are interpreted in terms of accountability, legitimacy, or perceived utility caused by the use of BWCs. Situational characteristics of the street segments explain why low-level street segments are affected by BWCs, while in hotspots no effect was detected.This is the author accepted manuscript. The final version is available from SAGE via https://doi.org/10.1177/109861111665372

Predictable Policing: Measuring the Crime Control Benefits of Hotspots Policing at Bus Stops

$\textit{Objectives}$ A fairly robust body of evidence suggests that hotspots policing is an effective crime prevention strategy. In this paper, we present contradictory evidence of a backfiring effect. $\textit{Methods}$ In a randomized controlled trial, aimed at reducing crime and disorder, London’s ‘hottest’ 102 bus-stops were targeted. Double patrol teams of Metropolitan Police Service uniformed officers visited the stops three times per shift (12:00–20:00), 5-times per week, for a duration of 15 min, over a 6 month period. Crucially, officers arrived and departed the bus stop on a bus, with significantly less time spent outside the bus stop setting. Outcomes were measured in terms of victim-generated crimes reported to the police and bus driver incident reports (DIRs), within targeted and catchment areas. We used adjusted Poisson-regression models to compare differences in pre- and post-treatment measures of outcomes and estimated-marginal-means to illustrate the treatment effect. $\textit{Results}$ DIRs went down significantly by 37 % ($\textit{p}$ = 0.07) in the near vicinity of the bus stops (50 m), by 40 % in the 100 m catchment area ($\textit{p}$ = 0.04) and marginally and non-significantly in the farthest catchment (10 %; $\textit{p}$ = 0.66), compared to control conditions. However, victim-generated crimes—the primary outcome measured in previous experiments—increased by 25 % ($\textit{p}$ = 0.10) in the near vicinity, by 23 % ($\textit{p}$ = 0.08) and 11 % ($\textit{p}$ $\leq$ 0.001) within the 100–150 m catchment areas, respectively. $\textit{Conclusions}$ These findings illustrate the role of bounded-rationality in everyday policing: reductions in crime are predicated on an elevated perceived risk-of-apprehension. Previous studies focused on clusters of addresses or public facilities, with police moving freely and unpredictably within the boundaries of the hotspot, but the patrol areas of officers in this experiment were limited to bus stops so offenders could anticipate their movements. Hotspots policing therefore backfires when offenders can systematically and accurately predict the temporal and spatial pattern of long-term targeting at a single location.This is the final version of the article. It first appeared from Springer via http://dx.doi.org/10.1007/s10940-016-9312-

Searching For Influential Actors in Co-Offending Networks: The Recruiter

The co-offending literature research has recently unraveled the possible existence of a specific class of offenders commonly referred to as a “recruiter”: one who recruits others who are younger or less experienced for the purpose of offending. Yet the available evidence has focused on small or non-representative samples, and has supplied a limited conceptual scope for explaining how instigation takes place within co-offending groups. We provide evidence from population-level arrest records over eight years in Sacramento, California, is presented on 251,285 criminal charges (n=80,245 offenders). Social network analysis to used to study how “crime ideas” are transmitted. We identified 1,092 recruiters, yet this subgroup is responsible for 6% of arrest cases in Sacramento and a disproportionate number of younger and less experienced recruits. The data suggest a pattern of recruitment specialization in specific crime categories and wider age differentials in against-persons rather than property crime categories. We contextualize the findings within Dawkin’s (1976) meme theory as a more robust conceptual framework for explaining how recruitment takes place, why “crime ideas” can be seen as units of imitation, and under which conditions they are subsequently replicated, reproduced, and evolve. Directions for future research are then considered, with an emphasis on crime control initiatives

'Lowering the threshold of effective deterrence'-Testing the effect of private security agents in public spaces on crime: A randomized controlled trial in a mass transit system.

Supplementing local police forces is a burgeoning multibillion-dollar private security industry. Millions of formal surveillance agents in public settings are tasked to act as preventative guardians, as their high visibility presence is hypothesized to create a deterrent threat to potential offenders. Yet, rigorous evidence is lacking. We randomly assigned all train stations in the South West of England that experienced crime into treatment and controls conditions over a six-month period. Treatment consisted of directed patrol by uniformed, unarmed security agents. Hand-held trackers on every agent yielded precise measurements of all patrol time in the stations. Count-based regression models, estimated marginal means and odds-ratios are used to assess the effect of these patrols on crimes reported to the police by victims, as well as new crimes detected by police officers. Outcomes are measured at both specified target locations to which security guards were instructed to attend, as well as at the entire station complexes. Analyses show that 41% more patrol visits and 29% more minutes spent by security agents at treatment compared to control stations led to a significant 16% reduction in victim-generated crimes at the entirety of the stations' complexes, with a 49% increase in police-generated detections at the target locations. The findings illustrate the efficacy of private policing for crime prevention theory

The Trick Doesn’t Work if You’ve Already Seen the Gorilla: How Anticipatory Effects Contaminate Pre-treatment Measures in Field Experiments

Objectives: When participants in experiments can anticipate the intervention, the study outcomes are said to be confounded. Ample evidence on intentional and unintentional interferences with the stimuli exists which suggests that participants tend to alter their response to the intervention prior to exposure to it; consequently, the measurement of post-treatment effects has been shown to be contaminated because there is a systematic interaction between measurement and treatment. However, an often-ignored consequence of such anticipatory effects is the impact on the baseline measure. If participants can anticipate the intervention early enough, the pretreatment scores will be conditional, therefore producing a biased estimate of the measure. We explore recent evidence on this bias and present a practical option for the mitigation of anticipatory effects. Methods: A review of the literature across multiple disciplines which addresses concerns regarding anticipatory effects. Results: Pretreatment measures, especially of the dependent variables at their baseline values, can be contaminated by anticipatory effects. We show that the major concerns experimenters should consider in this context are: (1) When can we say that the treatment effect ‘commenced’? (2) What forms the pretesting measure? (3) Are anticipatory effects case-specific or are there industry-wide, global anticipatory effects? (4) What can we conclude from studies whose pretest measures are affected by the anticipated treatment effect? and (5) What solutions are there for anticipatory effects? Conclusions: We outline arguments against the fundamental hypothesis that pre-treatment measurements of baseline measures are unaffected by the study conditions. The implications of anticipatory effects for both research and policy are often ignored, which may lead to erroneous conclusions regarding the treatment’s effectiveness, its benefits being underestimated, or both. The bias can be resolved by collecting ‘clean’ baseline measures prior to the commencement of the anticipatory effects, but the first step is to be aware of their potential

I heard it through the grapevine : A Randomized Controlled Trial on the Direct and Vicarious Effects of Preventative Specific Deterrence Initiatives in Criminal Networks

A rich body of literature exists on deterrence, yet little is known about how deterrence messages are communicated through social networks. This is an important gap in our understanding, because such communication gives rise to the possibility that social institutions can utilize the vicarious effect of the threat of punishment against one individual to reduce the rate of reoffending amongst their criminal associates. To test this, we identified criminals with an extensive offending history (prolific offenders) and their co-offenders using social network analysis and then conducted a randomized controlled trial to measure the effect on both prolific offenders and their cooffenders of delivering a “specific deterrence” message. The treatment— preemptive engagements with prolific offenders by a police officer offering both ‘carrots’ (desistance pathways) and ‘sticks’ (increased sanction threat)—was applied to the prolific offenders, but not to their co-offenders. The outcomes suggest that a single officer–offender engagement leads to a crime suppression effect in all comparisons, with 21.3%, 11.0%, and 15.0% reductions for specific, vicarious, and total network deterrence effects, respectively. The findings suggest that (a) social network analysis based on in-house police records can be used to cartographically understand social networks of offenders, with an aim of preventing crime; (b) deterrence messages promulgated by the police have the capacity to reduce crime beyond what was previously assumed, as the cascading of threats in cooffending relationships carries a vicarious crime reduction impact; (c) unlike “reactive specific deterrence” (i.e., a threat of punishment following a specific and detected crime) which can have perverse effects on certain offenders, preventative specific deterrence is a promising crime policy

"I heard it through the grapevine": A Randomized Controlled Trial on the Direct and Vicarious Effects of Preventative Specific Deterrence Initiatives in Criminal Networks

A rich body of literature exists on deterrence, yet little is known about how deterrence messages are communicated through social networks. This is an important gap in our understanding, because such communication gives rise to the possibility that social institutions can utilize the vicarious effect of the threat of punishment against one individual to reduce the rate of reoffending amongst their criminal associates. To test this, we identified criminals with an extensive offending history (“prolific offenders”) and their co-offenders using social network analysis and then conducted a randomized controlled trial to measure the effect on both prolific offenders and their co-offenders of delivering a “specific deterrence” message. The treatment—preemptive engagements with prolific offenders by a police officer offering both ‘carrots’ (desistance pathways) and ‘sticks’ (increased sanction threat)—was applied to the prolific offenders, but not to their co-offenders. The outcomes suggest that a single officer–offender engagement leads to a crime suppression effect in all comparisons, with 21.3%, 11.0%, and 15.0% reductions for specific, vicarious, and total network deterrence effects, respectively. The findings suggest that (a) social network analysis based on in-house police records can be used to prevent crime; (b) deterrence messages promulgated by the police have the capacity to reduce crime beyond what was previously assumed, as the cascading of threats in co-offending relationships carries a vicarious crime reduction impact; (c) unlike “reactive specific deterrence” (i.e., a threat of punishment following a specific and detected crime) which can have perverse effects on certain offenders, preventative specific deterrence is a promising crime policy.N/

Victims, offenders and victim-offender overlaps of knife crime: A social network analysis approach using police records.

Knife crime is a source of concern for the police in England and Wales, however little published research exists on this crime type. Who are the offenders who use knives to commit crime, when and why? Who are their victims, and is there a victim-offender overlap? What is the social network formation for people who are exposed to knife crime? Using a multidimensional approach, our aim is to answer these questions about one of England and Wales' largest jurisdictions: Thames Valley. We first provide a state-of-the-art narrative review of the knife crime literature, followed by an analysis of population-level data on central tendency and dispersion of knife crimes reported to the police (2015-2019), on offences, offenders, victims, victim-offender overlaps and gang-related assaults. Social network analysis was used to explore the formations of offender-victim networks. Our findings show that knife crime represents a small proportion of crime (1.86%) and is associated largely with violence offenses. 16-34 year-old white males are at greatest risk of being the victims, offenders or victim-offenders of knife crime, with similar relative risks between these three categories. Both knife offenders and victims are likely to have a criminal record. Knife crimes are usually not gang-related (less than 20%), and experienced mostly between strangers, with the altercation often a non-retaliatory 'one-off event'. Even gang-related knife crimes do not follow 'tit-for-tat' relationships-except when the individuals involved have extensive offending histories and then are likely to retaliate instantaneously. We conclude that while rare, an incident of knife crime remains predicable, as a substantial ratio of offenders and victims of future knife crime can be found in police records. Prevention strategies should not be focused on gang-related criminals, but on either prolific violent offenders or repeat victims who are known to the police-and therefore more susceptible to knife crime exposure

Random Assignment with a Smile: How to Love “TheRandomiser”

Abstract Objectives This note describes a free online portal (www.therandomiser.co.uk) that allows researchers to design randomised controlled trials and then delegate the random assignment process to pracademics delivering the experiment. Methods Observation of the use of this tool in repeated randomised trials in police agencies. Findings Researchers are able to design RCTs using the online portal, which offers many ways to customise the experimental design. Results are downloadable in excel or plain text format. Researchers can grant access to treatment providers, enabling them to log in securely, enter identifiers for cases, and assign different treatments to each case. Email notifications of assignment can be sent to designated list of recipients who can track the allocation of treatments. This tool delivers this functionality at zero cost and at the time of writing is being used by 78 researchers, who have set up 70 experiments that have processed 5778 randomisations. Conclusions TheRandomiser has been used in multiple experiments with feedback suggesting it is a powerful and user-friendly tool. The ability to deliver trickle-flow randomisation with high degrees of researcher control are attractive, as is the ability to edit an unlimited number of qualification questions prior to randomisation. </jats:sec

Highest Harm Crime “Recruiters” in a London Borough: a Case of Moving Targets

Abstract Research Question Can criminal recruiters be identified and ranked by crime harm levels in a London borough, and if so, how long is the predictive window of opportunity for targeting them with crime prevention efforts? Data This study deploys 5 years of Metropolitan Police Service crime data, relating to one of the 32 London boroughs in that time period. The data structure allowed identification of all suspects linked to the same crime report and all crime reports linked to the same suspects. Identification of linked suspects and their associated crime harm was undertaken using Structured Query Language (SQL) and ColdFusion Markup Language (CFML) via a web-based application. Methods All offenders were ranked by the number of co-offenders they acquired, as well as the total Cambridge crime harm index weight of the detected offences associated with them. Findings The highest harm recruiters are shown to be up to 137 times as harmful as the average offender, with one recruiter committing the same number of crimes as another but having 97 times more crime harm. Recruiter populations are highly dynamic, with few potential targets persisting from year to year over multiple years. Conclusions This study suggests that criminal recruiters are readily identifiable from police data, but police would only have a short window of opportunity to use deterrent or other preventive strategies with them once they are identified. </jats:sec