Police Resources Research Articles

And the Heat Goes On: Police Repression and the Modalities of Power

Among security institutions, police occupy a unique position. In addition to specializing in the repression of dissent, police monitor society and enforce order. Yet within research studying state repression, how police institutions are used and deployed to control domestic threats remain under-explored, particularly as it relates to the dual functionality just described. In this study, we develop and test an explanation of police repression accounting for the bifurcation of Mann’s two modalities of state power: infrastructural power and despotic power. Infrastructural power allocates police resources to surveil dissidents and preemptively limit dissent’s emergence or escalation. Police deploy despotic power through repressive responses to political threats. Empirically, we employ unique data to investigate police repression and the modalities of power in Guatemala. To analyze how shifting the balance between infrastructural and despotic power affects police repression, we isolate damage occurring from an earthquake that exogenously reshaped the landscape of infrastructural power. Results affirm the role of infrastructural power in regulating the despotic power of the state. Where local infrastructure was most affected by the earthquake, the security apparatus lost the capacity to surveil nascent movements and predict their activity, thereby providing opportunity for dissidents to mobilize and forcing police to (over-)react rather than shutdown resistance preemptively. However, the intensity of state violence recedes as the state recovers from the infrastructural damage and regains its control of local district.

PROTOCOL: Police stops to reduce crime: A systematic review.

PROTOCOL: Police stops to reduce crime: A systematic review.

Equity in the Police Districting Problem: Balancing Territorial and Racial Fairness in Patrolling Operations

ObjectivesThe Police Districting Problem concerns the definition of patrol districts that distribute police resources in a territory in such a way that high-risk areas receive more patrolling time than low-risk areas, according to a principle of territorial fairness. This results in patrolling configurations that are efficient and effective at controlling crime but that, at the same time, might exacerbate racial disparity in police stops and arrests. In this paper, an Equitable Police Districting Problem that combines crime-reduction effectiveness with racial fairness is proposed. The capability of this model in designing patrolling configurations that find a balance between territorial and racial fairness is assessed. Also, the trade-off between these two criteria is analyzed.MethodsThe Equitable Police Districting Problem is defined as a mixed-integer program. The objective function is formulated using Compromise Programming and Goal Programming. The model is validated on a real-world case study on the Central District of Madrid, Spain, and its solutions are compared to standard patrolling configurations currently used by the police.ResultsA trade-off between racial fairness and crime control is detected. However, the experiments show that including the proposed racial criterion in the optimization of patrol districts greatly improves racial fairness with limited detriment to the policing effectiveness. Also, the model produces solutions that dominate the patrolling configurations currently in use by the police.ConclusionsThe results show that the model successfully provides a quantitative evaluation of the trade-off between the criteria and is capable of defining patrolling configurations that are efficient in terms of both racial and territorial fairness.

Tracking Violent Crime with Ambulance Data: How Much Crime Goes Uncounted?

Research QuestionWhat proportion of ambulance records documenting injuries caused by criminal violence is included in police records for violent crimes occurring in the same area at the same dates and times as incidents found in ambulance records?DataWe analysed subsets of three datasets during matched time periods: West Midlands Ambulance Service records of all 36,639 incidents of violent injuries from January 2012 to March 2017; 132,317 West Midlands Police records of violent crimes from January 2012 to December 2015; and 9083 records of treatment of violent injuries as recorded in hospital Emergency Department (ED) records covering September 2013 to March 2016.MethodsWe compared all incidents in the ambulance dataset and ED data to corresponding locations and times in incidents recorded in police datasets.FindingsApproximately 90% of cases in the ambulance dataset did not have a corresponding case in the police dataset. The proportion was even lower in the Emergency Department dataset, where less than 5% of cases were successfully matched to a police record. These data suggest that adding the medical data to the police data could add 15 to 20% more violent offences to the totals recorded by the police.ConclusionsTracking identified ambulance data can add substantial numbers of serious violent crimes, over and above those reported to the police. These added cases can increase the targeting of police and public health resources to prevent harm against victims, at places, and by offenders at highest risk of serious violence.

Drug offence detection during the pandemic: An ARIMA analysis of rates and regional differences in Queensland, Australia

Public commentary has offered mixed opinion on the likely impact of COVID-19 restrictions on drug-related offending. On the one hand, it is argued that drug users – and the drug markets in which they interact – may have become the incidental targets of law enforcement as police seek to enforce social distancing regulations by focusing their efforts on street-level pedestrian activity or open-air gatherings. On the other, interstate border closures and restrictions on person and freight traffic are thought to have interrupted illicit drug supply chains, temporarily reducing or displacing market activity at the street level and thus reducing police detections of drug users. In this study, we extend current analyses of crime during the COVID-19 pandemic to explore how the rate of police detection for drug possession and other drug-related offences has changed. Using crime data from the Australian state of Queensland, we use Auto-Regressive Integrated and Moving Average time series modelling techniques to explore historical trends and their dynamic forecasts. We then compare actual offence rates for March through June to identify any statistically significant changes. We find that reported drug offences significantly vary across time and location highlighting that the impact of COVID-19 is not universal across Queensland. Thus, the significant heterogeneity in local drug market dynamics that has elsewhere been documented remains even in a major crisis with significant changes in policing activity and resource allocation. Our analysis has significant import for criminal justice practitioners in further understanding drug market dynamics and drug-related offending during COVID-19 restrictions.

Going Beyond the Blue: The Utility of Emergency Medical Services Data in Understanding Violent Crime

National victimization data suggest less than 50% of violent crime incidents are reported to the police. Official reports of crime to police, however, are often the only type of data used for the analysis of violence problems, the identification of geographic concentrations of violent crime, and the selection of targets for police and prevention resources. Yet, the question remains, are estimates of violent crime prevalence and location distorted from a unilateral reliance on police data? Here, we examine whether emergency medical service (EMS) data collected by the fire department are spatially concentrated in the same way as police data and whether these data can help identify instances of violence unreported to police in the city of Seattle between 2009 and 2011. We find high levels of concentration in both police and EMS data and evidence that new information is learned about the location of violence problems from utilizing multiple data sources. Overall, these findings contribute to a small but growing body of work that demonstrates the utility of nonconventional data in the identification of crime and harm concentrations of interest.

Policing the Pedal Rebels: A Case Study of Environmental Activism Under COVID-19

Australia, along with nation-states internationally, has entered a new phase of environmentally focused activism, with globalised, coordinated and social media-enabled environmental social movements seeking to address human-induced climate change and related issues such as the mass extinction of species and land clearing. Some environmental protest groups such as Extinction Rebellion (XR) have attracted significant political, media and popular commentary for their sometimes theatrical and disruptive forms of nonviolent protest and civil disobedience. Drawing on green and cultural criminology, this article constitutes an autoethnographic account of environmental protest during the final stages of the initial COVID-19 lockdown in NSW, Australia. It takes as a case study a small protest by an XR subgroup called the Pedal Rebels. The article explores the policing of environmental protest from an activist standpoint, highlighting the extraordinary police resources and powers mobilised to regulate a small peaceful group of 'socially distanced' protesters operating within the existing public health orders. It places an autoethnographic description of this protest in the context of policing practice and green and cultural criminology. Additionally, it outlines the way in which such policing is emboldened by changes to laws affecting environmental protest, making activism an increasingly risky activity. © The Author(s) 2021.

Safeguarding the Republic? The South African Police Service, Legitimacy and the Tribulations of Policing a Violent Democracy

Since 1994 the South African Police Service (SAPS) has undertaken various efforts to build legitimacy in South Africa. Extensive community policing resources have been made available, and a hybrid community-oriented programme (sector policing) has been pursued. Nevertheless, public opinion data has shown that there are low levels of public trust in the police. Using Goldsmith’s framework of trust-diminishing police behaviours, this article suggests that indifference, a lack of professionalism, incompetence and corruption on the part of the police, particularly in high-crime areas, have eroded public trust in the SAPS. Furthermore, in an effort to maintain order, reduce crime and assert the authority of the state, the police have adopted militaristic strategies and practices, which have contributed to numerous cases of excessive use of force, which has consequently weakened police legitimacy in South Africa

A Predictive Model for the Missing People Problem

The disappearance of people is a multidimensional phenomenon, in which several aspects must be considered. It affects people’s security perception and consumes police resources in its treatment. Therefore, does exists an emotional circumstance for the relatives of the missing person. At the same, the police departments must develop a search task, in most cases with much uncertainty. In this research, a predictive model to predict missing people’s status is presented. The information used to create the model come from the Colombian legal Medicine Institute, in a public dataset composed of 6202 cases and 11 variables. The output variable was the final disappearance status, with the categories Appears Dead, Appears Alive, and Still Disappeared. Three supervised machine-learning algorithms were trained and tested for the model creation, K-Nearest Neighbours, Decision Trees, and Random Forest. The study was divided into three phases, first considering all the output categories. In the second phase, generating a binary classification for the Appeared and Not appeared instance. Thirdly, models were built to predict the status of appeared persons, Appears Alive or Appears Dead. The K-NN algorithm outperforms the other models with an Area under the curve value of 94.8%.

Predicting the Type of Crime: Intelligence Gathering and Crime Analysis

Crimes are expected to rise with an increase in population and the rising gap between society’s income levels. Crimes contribute to a significant portion of the socioeconomic loss to any society, not only through its indirect damage to the social fabric and peace but also the more direct negative impacts on the economy, social parameters, and reputation of a nation. Policing and other preventive resources are limited and have to be utilized. The conventional methods are being superseded by more modern approaches of machine learning algorithms capable of making predictions where the relationships between the features and the outcomes are complex. Making it possible for such algorithms to provide indicators of specific areas that may become criminal hot-spots. These predictions can be used by policymakers and police personals alike to make effective and informed strategies that can curtail criminal activities and contribute to the nation’s development. This paper aims to predict factors that most affected crimes in Saudi Arabia by developing a machine learning model to predict an acceptable output value. Our results show that FAMD as features selection methods showed more accuracy on machine learning classifiers than the PCA method. The naïve Bayes classifier performs better than other classifiers on both features selections methods with an accuracy of 97.53% for FAMD, and PCA equals to 97.10%.

Equitable allocation of police human resources: Social Justice Coalition and Others v Minister of Police and Others

At the end of 2018, the Western Cape High Court handed down a ground-breaking judgment in the case of Social Justice Coalition and Others v Minister of Police and Others. The court held that the distribution of police personnel in the Western Cape unfairly discriminated against black and poor people on the basis of race and poverty. As the first case in South Africa recognising poverty as a discrete ground of discrimination, the judgment marks a significant development in the country’s equality rights jurisprudence. In addition, the court’s recognition that police distribution in the Western Cape is unfairly discriminatory has profound implications for the system of allocating police resources in that province, and potentially across the country. 
 In this case note I summarise the key issues in the case and offer an analysis of the court’s approach, arguing that while the case is to be lauded for its recognition of poverty as a ground of discrimination there are also some missed opportunities. Most significantly, the practical impact of the judgment has yet to be determined as the court limited its order to declaratory relief, requiring the parties to return to argue on the further practical remedy that should follow.

Policing vulnerability in sex work: the harm reduction compass model

ABSTRACT This paper explores the current approach to the interaction between policing and sex work in England and Wales. It reviews the legal and policy context and outlines current policing guidance and priorities, introducing the Harm Reduction Compass as a mechanism to advance policing policy and optimise operational decision-making. Through critical discussion of occupational culture and reforms in policing, it also assesses how continuity, reliability, and transferability can be achieved across police forces within the existing hostile and outdated statutory framework. The Harm Reduction Compass (HRC) aims to focus policing resources on adult sexual exploitation and crimes experienced by sex workers by decoding the complexities of different individuals’ personal circumstances. This paper proposes a new framework as a model to aid operational policing by triaging different scenarios to reach the most appropriate response. This new model, which identifies autonomy and harm as the most significant indicators, addresses harm and vulnerability holistically and combines policing with public health and community-based approaches; this ensures the pathway to assistance and intervention is an integrated multi-partnership. The HRC is a step forward in progressing police culture around the use of language and in dealing with crimes against sex workers in the most appropriate way.

Forecasting Crime? Algorithmic Prediction and the Doctrine of Police Entrapment

To predict criminal activity, police departments around the world are using technology at an accelerating rate. These “predictive technologies” produce predictions that direct police resources toward particular people and places for investigation. Using the doctrine of police entrapment recently considered by the Supreme Court of Canada in R v Ahmad, this paper explores whether and to what extent developments in the area of artificial intelligence can legitimately inform the creation of reasonable suspicions and bona fide inquiries in the entrapment context. It argues that due to a number of factors, including their lack of transparency, predictive technologies present difficult challenges for many stakeholders and weaken the defendant’s ability to argue entrapment. Although predictive technologies can be useful, their place in entrapment law complicates things for the existing entrapment framework. The paper suggests that the developing popularity of predictive technologies requires that the doctrine of entrapment be revisited.

An exploration of the use of tactical officers in three Canadian police services

In order to better understand the use of tactical police resources in Canada we interviewed patrol and tactical officers ( N = 28) from three Canadian police services. A thematic analysis indicated that tactical officers are primarily responding to calls beyond the capabilities of patrol to resolve optimally which included high-risk calls as denoted by the presence of risk-factors and calls unfolding in special environments. Further, tactical officer response is thought to result in a reduced threat to officer and public safety. Our findings suggest that in contrast to previous claims, tactical officers are often responding to calls where significant risk is present.

Focused Deterrence and Program Fidelity: Evaluating the Impact of Detroit Ceasefire

Focused deterrence programs, which concentrate community and police resources on small groups of high-risk offenders, have been identified in a number of cities as an effective method to reduce violent crime. In 2013, the city of Detroit began its own “Ceasefire” program in two of its most violent police precincts, which continued through 2019. This study examines the community-level effect of the 2013–2019 Detroit Ceasefire initiative on fatal and non-fatal shooting victimization. We apply a synthetic control design to account for the complex, disaggregated data to identify the effect of Ceasefire above and beyond the substantial decreases in gun violence observed throughout Detroit. We find marginal decreases in victimizations among those aged 15-24 and 25-34 in the year after Ceasefire was re-organized in 2015, but these effects were limited and largely converged to trends observed in the rest of the city. We discuss the results of this evaluation with a focus on the importance of effective implementation as well as the challenges of studying violence prevention strategies under ever evolving conditions.

Designing an Explainable Predictive Policing Model to Forecast Police Workforce Distribution in Cities

Despite extensive research, measurable benefits of predictive policing are scarce. We argue that powerful models might not always help the work of officers. Furthermore, developed models are often unexplainable, leading to trust issues between police intuition and machine-made prediction. We use a joint approach, mixing criminology and data science knowledge, to design an explainable predictive policing model. The proposed model (a set of explainable decision trees) can predict police resource requirement across the city and explain this prediction based on human-understandable cues (i.e., past event information, weather, and socio-demographic information). The explainable decision tree is then compared to a non-explainable model (i.e., a neural network) to compare performance. Analyzing the decision tree behaviour revealed multiple relations with established criminology knowledge. Weather and recent event distribution were found to be the most useful predictors of police workforce resource. Despite wide research showing relationships between socio-demographic information and police activity, socio-demographic information did not contribute much to the model’s performance. Though there is a lack of research on measurable effects of predictive policing applications, we argue that combining human instinct with machine prediction reduces risks of human knowledge loss, machine bias, and lack of confidence in the system.

Women police stations: have they fulfilled their promise?

ABSTRACT Women police stations (WPS) are recognized as an important component of gender-sensitive policing for dealing with domestic violence (DV). These stations have been established in many developing countries to serve two main purposes: to deal better with crimes against women and to provide a rewarding career for women officers. This paper examines whether WPS have met these expectations. At a time when other countries are thinking about introducing WPS, it is important to validate best practices and identify shortcomings for better use of police and public resources in dealing with DV and other crimes against women. We describe the structure and functioning of the stations based on interviews, review pertinent studies and analyze official data to explain the role of the WPS in empowering victims; improving their access to justice; reducing victimization and increasing the representation of women in policing. Theory, policy and research implications are discussed.

A Comparison of Attribute-Focused and Harm-Focused Methods for Assessing the Risk of Organized Crime Groups: Are They in Agreement?

Abstract Risk assessment methods are used to map the threat posed by organized crime and assist in the prioritization of policing resources. Within policing, risk assessment methods are currently in use that either focus on the attributes of organized crime groups or the types of harm posed. Statistical analysis was undertaken of risk assessment data produced using one attribute-focused and one harm-focused method. The study was based on a non-random sample of 113 attribute-focused and 77 harm-focused risk assessments of the same 17 OCGs, and a sub-sample of 36 pairs of risk assessments of 16 of the OCGs. A moderate correlation was found between the two methods, despite differences in their risk assessment processes. Lower levels of agreement tended to be associated with OCGs posing high levels of harm, particularly financial and psychological. Using the two risk assessment methods in combination is proposed as a way of building consensus that draws on their alternative perspectives. The techniques applied in this analysis could be used to inform revisions to the methods and their supporting materials, identify outlying risk assessments, and potentially incorporate other information sources such as harm indices.

Mathematical analysis of crime dynamics in and out of prisons

Recently, there have been many attempts to develop a mathematical model that captures the nature of crime. One of the successful models has been based on diffusion‐type differential equations that describe how criminals spread in a specific area. Here, we propose a dynamic model that focuses on the effect of interactions between distinct types of criminals. The accumulated criminal records show that serious and minor crimes differ in many measures and are related in a complex way. While some of those who have committed minor crime spontaneously evolve into serious criminals, the transition from minor crime to major crime involves many social factors and has not been fully understood yet. In this work, we present a mathematical model to describe how minor criminals turn into major criminals inside and outside of prisons. The model assumes that a population can be divided into a set of compartments, according to the level of crime and whether arrested or not, and individuals have equal probability to change compartment. The model is design to implement two social effects which respectively have been conceptualized in popular terms “broken windows effect” and “prison as a crime school.” Analysis of the system shows how the crime‐related parameters such as the arrest rate, the period of imprisonment, and the in‐prison contact rate affect the criminal distribution at equilibrium. Without proper control of contact between prisoners, the longer imprisonment rather increases occurrence of serious crimes in society. An optimal allocation of the police resources to suppress crimes is also discussed.

Not collateral damage: Trends in violence and hate crimes experienced by sex workers in the Republic of Ireland

The Republic of Ireland’s new Criminal Law (Sexual Offences) Act 2017 (2017 Act) criminalised sex purchase. Drawing on primary data from reports made by sex workers in Ireland to UglyMugs.ie, we analyse trends in violent and other crimes against sex workers in Republic of Ireland (hereafter Ireland). Examining the four-year period 2015–2019, we highlight the various crimes sex workers experience, including incidents of hate crime. Analysis of UglyMugs.ie data found that crimes (including violent offences) against sex workers increased following the introduction of the new law and continued with low levels of reporting of said crimes to the police. The data suggest that the 2017 Act heightens the risks for sex workers. Here, we advocate an intersectional framework to provide a more nuanced understanding of how sex workers in Ireland experience violent and other hate crimes (ICRSE, 2014). We suggest that considering the international research evidence, the most conducive framework in which to reduce violence against sex workers is that of full decriminalisation ( Platt et al, 2018 ). But, as others have pointed out, that legal reform needs to be in tandem with other policies and a refocusing of police resources on sex worker safety, better enabling reporting and access to justice.