Police Resources Research Articles

Case closed – Wrappings and encasement delays and reduces fly presence on body parts

Homicide, particularly where a body has been concealed, is uniquely challenging for investigators to estimate the time of occurrence due to the methods employed by perpetrators to hide the body or its constituent parts from detection. The regularity of necrophagous insect lifecycles to determine minimum post-mortem interval (minPMI) is widely employed but remains an unreliable technique if used without a clear understanding of the factors that affect insect access and oviposition behaviour to concealed remains.The purpose of this study was to investigate the effect of wrapping body parts on fly colonisation and implications for minPMI calculations. Field studies were carried out using four treatments of pork (as surrogate body parts), in five replicates, one unwrapped, the other three wrapped in either a black plastic sack, a small-zipped wash bag (to simulate a suitcase), or a plastic sack further placed in a wash bag. Over a 48-h period all the methods of wrapping significantly disrupted the host-finding process of blowflies to dismembered carcasses, with a delay of initial contact and oviposition of 30+h (dependant on wrapping) and even more in wet conditions (48+ h). Egg numbers were also reduced by as much as 99.1% on wrapped samples compared to unwrapped. These new findings highlight the importance of applying adjustments to minPMI calculations when encountering wrapped remains. Advances in the accuracy of minPMI calculations will prevent the waste of valuable police time and resources and better focus the search for witnesses and suspects in homicide investigations.

Strategic management in the police force's organizational culture

This paper examines which economically oriented methods and approaches to strategic management may be found in the police's organizational culture, which is often disconnected from economic knowledge. In addition, the economic question of how far strategic considerations and strategic management expertise are currently embedded in the police's organizational culture and incorporated into their decision-making processes is addressed. The focus of the research is on the decision-making processes around the acquisition of a single police resource. This is a piece of a larger strategic decision that must be taken in principle and is based on the author's earlier risk assessment of a police resource. An detailed literature review is undertaken for this aim, which is confined to only the most recent literature sources. In addition, existing sources that communicate internal German police opinions are consulted. Given the difficulty of such a task, four responses to parliamentary questions from German interior ministries, as well as the experiences of European police forces on the subject, were employed. In this context, it is worth noting that the police and its members are dealing with a rising proclivity for violence, as well as a loss of reputation from segments of the populace who are becoming increasingly critical across borders. The author finds that strategic management is not yet fully entrenched in the police force, but it is on the rise, based on his research. As the essay will demonstrate, the previously asked scientific question can therefore only be answered in a contradictory manner.

Spatial distribution and developmental trajectories of crime versus crime severity: do not abandon the count-based model just yet

Purpose/backgroundA new body of research that focuses on crime harm scores rather than counts of crime incidents has emerged. Specifically in the context of spatial analysis of crime, focusing on crime harm suggests that harm is more concentrated than counts, at the level of crime hot spots. It remains presently unclear what drives the concentration distributions, and whether the count-based model should be abandoned.MethodsCross-sectional and longitudinal analysis of 6 year of spatiotemporal crime data in Toronto, Canada, to compare patterns and concentration of crime harm (measured in terms of the Crime Severity Index (CSI) against crime counts. Conditional probabilities, trajectory analyses, power few concentrations, and spatial Global Moran’s I are used to infer generalised trends from the data.FindingsOverall CSI and crime counts tend to exhibit similar concentrations at the spatial micro levels, except against-the-body crimes such as violence which seems to drive nearly all the variations between the two measurement types. Violence harm spots tend to be more dispersed citywide and often do not remain constant year-to-year, whereas overall crime hotspots are more stable over time. Nevertheless, variations in disproportionally high crime hot spots are associated with total variations in crime, with as little as 1% increase in crime levels in these hot spots translating into substantial overall gains in recorded crime citywide.ConclusionsAbandoning count-based models in spatial analysis of crime can lead to an incomplete picture of crime concentrations. Both models are needed not just for understanding spatial crime distributions but also for cost-effective allocation of policing resources.

Police equilibrium: a glocal assessment of the demand and supply of police

ABSTRACT Police resources are scarce public goods and have to be used with maximum efficiency. One dimension of efficiency is the spatial and temporal alignment of police presence to calls-for-service. The research question of interest in this paper is whether the police are where and when they are needed most. We employ a supply and demand model based on police presence and the occurrence of calls for police service. We use GPS data from 100 tracked police vehicles and data on calls-for-service from a mid-sized European police agency. We find that most segments receive relatively more police presence than calls-for-service alone would warrant and that calls-for-service as well as emergency calls show little spatiotemporal variation. Further, police presence is found to be the main driver in changes regarding police provision across streets. We discuss the need to develop more evidence-based frameworks to investigate the effectiveness of police patrol and response deployment. The insights can assist police chiefs to identify streets with high demand for police services and to understand the predictability of police demand within their jurisdiction.

Smart Patrolling Based on Spatial-Temporal Information Using Machine Learning

With the aim of improving security in cities and reducing the number of crimes, this research proposes an algorithm that combines artificial intelligence (AI) and machine learning (ML) techniques to generate police patrol routes. Real data on crimes reported in Quito City, Ecuador, during 2017 are used. The algorithm, which consists of four stages, combines spatial and temporal information. First, crimes are grouped around the points with the highest concentration of felonies, and future hotspots are predicted. Then, the probability of crimes committed in any of those areas at a time slot is studied. This information is combined with the spatial way-points to obtain real surveillance routes through a fuzzy decision system, that considers distance and time (computed with the OpenStreetMap API), and probability. Computing time has been analized and routes have been compared with those proposed by an expert. The results prove that using spatial–temporal information allows the design of patrolling routes in an effective way and thus, improves citizen security and decreases spending on police resources.

Crime in a Time of Cannabis: Estimating the Effect of Legalizing Marijuana on Crime Rates in Colorado and Washington Using the Synthetic Control Method

The legalization of marijuana for recreational use continues to expand across America. Colorado and Washington were the first states to legalize marijuana in 2012. A primary concern regarding legalization is how these policy changes affect crime rates. Researchers have begun to estimate the effect marijuana legalization has had on crime rates. We extend this literature by using a different analytical approach. State level data covering years 2000–2019 were analyzed using the synthetic control method to find that legalizing marijuana for recreational use in Colorado and Washington was generally not associated with variations in index crime rates. These findings substantiate prior research. Increased crime rates should not be a primary concern as more states move to adopt recreational marijuana use legislation. Instead, the benefits to states via harm reduction, increased tax revenue, and a more efficient allocation of policing resources ought to be more of a consideration for states when passing recreational marijuana legislation.

“Hot street” of crime detection in London borough and lockdown impacts

ABSTRACT In recent years, the police intervention strategy “Hot spots policing” has been effective in combating crimes. However, as cities are under the intense pressure of increasing crime and scarce police resources, police patrols are expected to target more accurately at finer geographic units rather than ballpark “hot spot” areas. This study aims to develop an algorithm using geographic information to detect crime patterns at street level, the so-called “hot street”, to further assist the Criminal Investigation Department (CID) in capturing crime change and transitive moments efficiently. The algorithm applies Kernel Density Estimation (KDE) technique onto street networks, rather than traditional areal units, in one case study borough in London; it then maps the detected crime “hot streets” by crime type. It was found that the algorithm could successfully generate “hot street” maps for Law Enforcement Agencies (LEAs), enabling more effective allocation of police patrolling; and bear enough resilience itself for the Strategic Crime Analysis (SCA) team’s sustainable utilization, by either updating the inputs with latest data or modifying the model parameters (i.e. the kernel function, and the range of spillover). Moreover, this study explores contextual characteristics of crime “hot streets” by applying various regression models, in recognition of the best fitted Geographically Weighted Regression (GWR) model, encompassing eight significant contextual factors with their varied effects on crimes at different streets. Having discussed the impact of lockdown on crime rates, it was apparent that the land-use driven mobility change during lockdown was a fundamental reason for changes in crime. Overall, these research findings have provided evidence and practical suggestions for crime prevention to local governors and policy practitioners, through more optimal urban planning (e.g. Low Traffic Neighborhoods), proactive policing (e.g. in the listed top 10 “Hot Streets” of crime), publicizing of laws and regulations, and installations of security infrastructures (e.g. CCTV cameras and traffic signals).

Locating offenders: Introducing the reverse spatial patterning approach

ObjectivesCurrent strategies for locating where offenders live either focus exclusively on individual suspects or generalize to entire neighborhoods. However, better estimates of where offenders are located may improve models of the ecological distribution of crime, and forecasts of the locations of future crime incidents. MethodsWe propose a novel reverse spatial patterning (RSP) strategy that estimates where offenders may live based on the spatial locations of crime events. We rely on a distance decay function – based on the consistent finding that offenders do not travel far to commit crime – and Hipp's (2016) general theory of spatial crime patterns, to work backwards from the locations of actual crime events to make predictions about where offenders may live in subsequent years. We then use these estimates in models predicting crime locations. We create two versions of the RSP: one which assumes everyone is equally likely to offend, and another that creates an estimate assuming disproportionate offending across persons. ResultsWe test the effectiveness of our proposed strategy for these two measures using offense and arrest data from St. Petersburg, FL, and assess how well they predict the location of offenders (proxied by arrestees) and future crime events. We find consistent evidence that our RSP strategy provides better predictions of the locations of where offenders are located and also future crime incidents across a variety of crime types compared to existing strategies. ConclusionThe RSP approach is useful for creating estimates of where offenders live, which allow for better predictions of the locations of future crime incidents. These better forecasts will allow for more efficient allocation of police resources and targeted crime suppression efforts.

Seafarers on the shore: issues raised by Australian doctors treating seafarers.

Seafarers on the shore: issues raised by Australian doctors treating seafarers.

Early Detection of Suspicious Behaviors for Safe Residence from Movement Trajectory Data

Early detection of people’s suspicious behaviors can aid in the prevention of crimes and make the community safer. Existing methods that are focused on identifying abnormal behaviors from video surveillance that are based on computer vision, which are more suitable for detecting ongoing behaviors. While criminals intend to avoid abnormal behaviors under surveillance, their suspicious behaviors prior to crimes will be unconsciously reflected in the trajectories. Herein, we characterize several suspicious behaviors from unusual movement patterns, unusual behaviors, and unusual gatherings of people, and analyze their features that are hidden in the trajectory data. Meanwhile, the algorithms for suspicious behavior detection are proposed based on the main features of the corresponding behavior, which employ spatiotemporal clustering, semantic annotation, outlier detection, and other methods. A practical trajectory dataset (i.e., TucityLife) containing more than 1000 suspicious behaviors was collected, and experiments were conducted to verify the effectiveness of the proposed method. The results indicate that the proposed method for suspicious behavior detection has a recall of 93.5% and a precision of 87.6%, demonstrating its excellent performance in identifying the possible offenders and potential target places. The proposed methods are valuable for preventing city crime and supporting the appropriate allocation of police resources.

THE INJUSTICE OF UNDER-POLICING IN AMERICA

THE INJUSTICE OF UNDER-POLICING IN AMERICA

The application of TreadMatch scans to aid the process of footwear mark comparison

Currently in the UK, if a person is arrested or charged with a recordable offence, they can have prints of their footwear taken whilst in custody. The tread pattern recorded in these prints can be searched for using the National Footwear Database to find out if the same footwear pattern has been recovered at previous crime scenes, generating forensic intelligence.TreadMatch is a digitised system for collecting footwear prints seized from detainees in custody for this purpose. Whilst its use for generating intelligence is accepted, validation experiments have not been conducted to understand its level of performance in assisting in forensic comparison purposes for identification, because in the absence of an incorporated scale, it is not known how well TreadMatch reproduces the pattern size of a tread, threatening the validity of the comparison. If it can be determined that the measurements of TreadMatch scans are consistent with the more commonly used aluminium powder test marks, this could save Police time and resources if the digital scans could be used for preliminary assessment prior to the footwear being physically submitted for evidential comparison. Therefore, this study set out to compare three different types of TreadMatch scans (‘dynamic’, ‘zoomed’ and ‘rolled’) for thirty different pieces of footwear, with test marks of the same footwear using the traditional method (fingerprint powder). Length and width measurements were obtained from each tread pattern using GNU Image Manipulation Program software. The resulting data were analysed to assess for agreement between TreadMatch scans and test marks using 95% Intraclass Correlation Coefficients (ICC) and 95% Bland-Altman plots of Limits of Agreement (LOA). Additionally, an intra-sample study using fifteen repeated measurements of the same piece of footwear for different TreadMatch scanning methods was carried out to support the larger validity study.95% ICC3,1 resulted in coefficients ranging from 0.99 to 1.00 across all measurements. 95% LOA displayed close agreement. There was less agreement and more variation displayed between the test marks and the TreadMatch rolled scans for both length and width measurements. This variation for hand-rolled prints must be taken into consideration and a standard approach developed. The study suggests TreadMatch can be used for preliminary assessments in assisting forensic comparisons, particularly for dynamic and zoomed prints.

Police resource distribution in China: spatial decision making based on PGIS-MCDA method

PurposeBased on the theoretical viewpoints of criminal geography and environmental criminology, this research uses spatial multi-criteria decision-making methods. In the process of spatial decision-making and optimization of police resources, researchers fully consider the dynamic application of Geographic Information System (GIS) and the effects of spatial prevention and control.Design/methodology/approachResearchers use an integrated method combining Policing Geographic Information System (PGIS) and multi-criteria decision analysis (MCDA). On the one hand, police GIS has an excellent visual data analysis platform and integrated decision support system in data management, spatial analysis, data exploration and regression analysis. On the other hand, through the design of the indicator system, the quantification of indicators, the determination of weights, comprehensive evaluation and sensitivity analysis, MCDA can select the best plan from a large number of alternatives. When joining MCDA, the spatial dimension will bring the research results closer to the real world.FindingsThe study finds that the crime of burglary is affected to a certain extent by the distribution of police forces, the location of police units. Another important finding of this research is the correlation between more precise preventive measures and the crime of burglary.Originality/valueFrom a practical point of view, this research would help advance the role of police units and law enforcement agencies in preventing burglary crimes and provide experience for the allocation of regional police resources.

A mixed-methods evaluation of the one-way door and CitySafe patrol policies in Whangarei, New Zealand.

In this paper, we evaluate the impacts of one-way door and CitySafe patrol policies in Whangarei, New Zealand, using a mixed-methods approach. In the quantitative analyses, we apply interrupted time series analysis and difference-in-differences analysis to data on antisocial behaviour derived from CCTV footage, and to police calls-for-service data. In the qualitative analysis, we apply thematic analysis to data from semi-structured interviews with 33 local stakeholders. We find a statistically significant increase in observed antisocial behaviour, but statistically significant decreases in violence and drug and alcohol offences, except when other small cities are used as a control group. In the qualitative analysis, a large majority of interviewees thought that the policy had reduced alcohol-related harm and increased safety, although a number of possible unintended consequences were also noted, including a reallocation of police resources, a redistribution of night-time drinking towards the suburbs, and a change in the demand for taxi companies. Overall, there is evidence only that the policies have reduced perceived alcohol-related harm, rather than reducing measures of harm.

Enforcement of COVID-19 pandemic lockdown orders in Nigeria: Evidence of public (non)compliance and police illegalities

Given the public resentment that trailed the unprecedented lockdown order enforced as a public health emergency control strategy to contain the spread of Coronavirus Disease (COVID-19) pandemic, this study explored citizens' compliance with the order and how its enforcement occasioned illegal police practices in Nigeria. With a qualitative approach, this study recruited 90 participants using varieties of sampling methods to understand public behaviour and police conduct in the enforcement of the order. From the insights gathered with a semi-structured interview and analysed with the thematic analysis method, the study observed that economic hardship, unavoidable matters from the citizens’ end and mistrust of authorities fueled non-compliance. Such mistrust amplified misinformation during the pandemic. Although there was a reasonable level of compliance, the pre-existing police illegalities (extortion and bribery) facilitated the cases of non-compliance in Nigeria. Also, hostility ensued between police personnel and citizens during the enforcement of the lockdown. Therefore, this study advised the government and stakeholders on the imperatives of adequate socio-economic preparations, emphasising public trust and the provision of relief materials. Additionally, it suggested to the police authorities reform ideas to better equip, monitor, and manage police resources for effective handling of future pandemics.

Seasonal mobility of populations and allocation of police resources in Finland

This study analyses the impact of the seasonal mobility of populations on the emergency response times (ERT) of the police. The concept of multi-locality increases the mobility of people but, however, the public service structures of the society and different administrative systems do not sufficiently account for that. The results of the mixed-model regression demonstrate the challenges in the police resources allocation when people are acting in different areas than expected. Emergency response times was lengthened as the seasonal population increased and spatially dispersed over the regions during the seasons. We suggest that the seasonal mobility should be involved the future planning process of police resource allocation.

Hot spots and burning times: A spatiotemporal analysis of calls for service to establish police demand

Establishing police demand is important to optimally allocate scarce police resources in space and time. To contribute to the existing knowledge on the optimization of policing and crime prevention strategies worldwide, we examine the spatiotemporal pattern of calls for service (CFS), with a focus on the urgency of the calls (as measured by the police priority codes), in Antwerp (2017–2020), Belgium. To disentangle the space-time pattern of the priority codes, we apply the average nearest neighbour statistic, global and local Moran's I, Getis-Ord Gi*, and emerging hot spot analysis. Our results demonstrate that the spatial, temporal, and space-time patterns of the priority codes differ and that more urgent CFS are more demanding in terms of allocated police vehicles than less urgent CFS. Based on the findings of this paper, we recommend to include priority codes in future police patrol routing solutions to make patrol strategies more realistic. An important aspect will be to increase/decrease the number of available units depending on the spatiotemporal pattern of the CFS per priority code. Instead of only working with fixed shifts, there is a need to deploy peak shifts during times of peak demand.

Shutting the Gate: A Preliminary Study of Farm Crime Prevention Methods Used by the Police in Rural England and Wales

Rural crime is an issue for farms across the United Kingdom. The costs of farm crime are at their highest level in eight years and impact on both farmers and consumers. Past research has examined farmers' attitudes towards farm crime prevention but the attitudes of the police have been little explored. Police forces in rural England and Wales were surveyed about their views on farm crime prevention (e.g. prevention methods used, efficacy of methods, future of farm crime prevention). Traditional and community-based prevention methods such as regular patrols, proactive operations, prevention initiatives and community education were widely used, as were technological prevention methods such as CCTV. Just over half of respondents perceived these methods to be effective though concerns were raised that their efficacy was affected by limited police resources. The majority of respondents felt that the future of farm crime prevention would involve better physical security, more CCTV and more crime prevention initiatives.

Ethics as part of police management

This article examines which ethical features can be found in the police's more economically oriented management tactics, as well as the extent to which ethical considerations are factored into police decision-making processes. In this approach, the article builds on the author’s previous work, which focused on a police resource's risk assessment. The goal of this research is to answer the scientific question of whether or not harmful police trends could have been detected sooner. In this context, it's worth noting that the police force and its members are under a lot of moral and ethical criticism from a population that's becoming increasingly critical across borders. The author concludes that every police officer's moral compass can really provide a foundation for police activity, based on a literature study and a secondary quantitative content analysis. It is demonstrated that, in terms of duty ethics, ethical features are heavily reliant on role models. However, such role models are not always available. Supervisors, on the other hand, do not always live up to their responsibility as role models. Professional ethics are being implemented and strengthened in the training of young police recruits, which is positive. It is intended that ethical considerations would become more prevalent in the police force.

An Integrated Graph Model for Spatial–Temporal Urban Crime Prediction Based on Attention Mechanism

Crime issues have been attracting widespread attention from citizens and managers of cities due to their unexpected and massive consequences. As an effective technique to prevent and control urban crimes, the data-driven spatial–temporal crime prediction can provide reasonable estimations associated with the crime hotspot. It thus contributes to the decision making of relevant departments under limited resources, as well as promotes civilized urban development. However, the deficient performance in the aspect of the daily spatial–temporal crime prediction at the urban-district-scale needs to be further resolved, which serves as a critical role in police resource allocation. In order to establish a practical and effective daily crime prediction framework at an urban police-district-scale, an “online” integrated graph model is proposed. A residual neural network (ResNet), graph convolutional network (GCN), and long short-term memory (LSTM) are integrated with an attention mechanism in the proposed model to extract and fuse the spatial–temporal features, topological graphs, and external features. Then, the “online” integrated graph model is validated by daily theft and assault data within 22 police districts in the city of Chicago, US from 1 January 2015 to 7 January 2020. Additionally, several widely used baseline models, including autoregressive integrated moving average (ARIMA), ridge regression, support vector regression (SVR), random forest, extreme gradient boosting (XGBoost), LSTM, convolutional neural network (CNN), and Conv-LSTM models, are compared with the proposed model from a quantitative point of view by using the same dataset. The results show that the predicted spatial–temporal patterns by the proposed model are close to the observations. Moreover, the integrated graph model performs more accurately since it has lower average values of the mean absolute error (MAE) and root mean square error (RMSE) than the other eight models. Therefore, the proposed model has great potential in supporting the decision making for the police in the fields of patrolling and investigation, as well as resource allocation.