Robbery Incidents Research Articles

POLICIAMENTO PREDITIVO E INTELIGÊNCIA ARTIFICIAL: ANÁLISE DE DESEMPENHO DO ALGORITMO DE APRENDIZADO DE MÁQUINA SUPERVISIONADO RANDOM FOREST NA PREDIÇÃO DE OCORRÊNCIAS POLICIAIS DE ROUBO NAS ZONAS DA REGIÃO METROPOLITANA DE SÃO LUÍS

Predictive policing is a concept based on the premise that it is possible to predict when and where crimes will occur again in the future by using sophisticated computer analysis based on data from previously committed crimes (UCHIDA, as cited in NORTON, 2013, pp. 32–33). The aim of this article is to analyze the spatial prediction of crimes, highlighting the importance of innovative approaches in the field of public safety management. Specifically, the article explores practical applications of using Artificial Intelligence (AI) through supervised machine learning algorithms for classification, using the emergency call records database (190) of robbery incidents in the metropolitan region of São Luís as input, and comparing results through validation techniques for the Random Forest algorithm. Through detailed analysis of these data, the potential of predictive policing is illustrated not only to anticipate criminal events but also to develop a computational tool capable of assisting and supporting strategic decision-making, significantly contributing to troop allocation management and, consequently, to the enhancement of preventive urban patrol services.

Marginal deterrence: The effect of illicit incentive on robbery escalation

The extant literature on marginal deterrence supports the notion that individuals maintain a dynamic decision-making process that yields several ranked outcomes after weighing the risks and rewards. In this article, we conduct a novel large-scale empirical analysis of the marginal deterrence principle to advance theory on the magnitude of potential deterrent effects. We regress a stratified outcome variable representative of six decision outcomes for the crime of robbery on a unique exogenous illicit incentive measure. We employ a multilevel ordinal regression equation that nests 29,297 robbery incidents within 98 cities to test the marginal deterrence thesis. Our analysis yields a statistically significant positive relationship with our criminogenic incentive measure. More specifically, the model provides suggestive evidence that as the illicit incentive increases the odds of violence escalating in a robbery incident also increases. The results from this analysis provides theoretical, methodological, and practical implications for attenuating societal harm. Moreover, we expand on how to measure the scaling severity of harm within the criminal decision-making process. From a policy perspective, we provide support for harm indices and crime prevention.

A Bayesian network-based tool for crisis classification in piracy or armed robbery incidents on passenger ships

Piracy and armed robbery continue to pose significant security threats to the shipping industry. This paper presents a real-time threat assessment and crisis classification tool for piracy or armed robbery incidents. The tool is part of a crisis classification module that addresses various categories of security threats. This module is currently being developed as part of the EU-funded research project ISOLA, which aims to introduce an intelligent security superintendence ecosystem. The ecosystem is designed to complement the existing ship security processes and measures applied onboard passenger ships. The tool operates by providing real-time threat classification and subsequent warnings by analysing data collected from the ship’s legacy systems and installed sensors with the utilisation of Bayesian probabilistic techniques, particularly Bayesian Networks. The BN model developed for this purpose is thoroughly examined, and its validation is presented through indicative case studies involving piracy and armed robbery. The main objective is to improve situational awareness, enhance vigilance and early threat detection, and support the decision-making process for the Master and crew, especially under time-sensitive circumstances and stressful conditions.

Effect ofthe NFL's Super Bowl on emergency department visits for assault-related injuries.

Through its associations with mass gatherings, alcohol consumption, emotional cues, and gambling, the Super Bowl (SB) has been implicated in increased rates of interpersonal violence and assaults. This study endeavors to investigate the relationship between assault-related injuries, especially intimate partner violence (IPV) and SB. A retrospective review of prospectively collected data from the National Electronic Injury Surveillance System (NEISS) spanning 2005 to 2017 was conducted. Assault-related injuries were examined in relation to (1) the 4-day Super Bowl weekend (Friday-Monday), (2) Super Bowl Sunday, and (3) the Super Bowl week (Friday-Thursday) for all years, following the loss of the projected winning team (underdog victories), and losses despite a significant point spread favoring one team (upset losses). National estimates of injuries and associated variables were derived using the SUDAAN software. While there were no significant differences in the overall number of assaults or assault types during the SB weekend (5.6% vs 5.5%; p = 0.31), relative decreases were observed for altercations (21.1% vs 24.8%; p < 0.01), sexual assault (3.4% vs 4.0%; p < 0.01), and IPV (8.3% vs 12.5%; p < 0.01) on the Friday preceding SB, and robbery incidents on SB Sunday (2.1% vs 3.5%; p = 0.01). No changes in the incidence of assault-related injuries were found based on the favored or underdog status of the teams, including upset losses. Contrary to expectations, SB was not associated with increased assault-related injuries. This study underscores the need for year-round structural changes in addressing violence rather than relying solely on heightened awareness during specific events.

Risk Terrain and Multilevel Modeling of Street Robbery Distribution in Baltimore City

The structure and functions of neighborhoods determine the impact of measures used to estimate the distribution of street robbery across space and time. The risk of street robbery could vary between different sections of the area. Prior research has typically relied on one-dimensional analysis, which sparsely accounts for the hierarchical configuration of a neighborhood’s influence on spatial crime distribution. Much less is known about how the predictor variables moderate each other at different neighborhood levels. Data was collected from 13,789 US Census blocks ( N = 13,788) aggregated to administrative neighborhoods ( N = 278) to examine how neighborhood structure affects street robbery distribution at two spatial levels. A Risk Terrain Model was adopted to develop a physical environment risk measure—Aggregate Neighborhood Risk of Crime (ANROC), which, alongside sociodemographic risk factors, predicted the outcomes of the Negative Binomial General Linear Regression models. Study findings suggest that individual-level (block) and group (neighborhood) level predictors influenced street robbery. Both group-level physical environment and total population moderated the impact of the individual-level physical environment on street robbery incidents.

Inflation-Crime Nexus: A Predictive Analysis of Crime Rate Using Inflationary Indicator in Municipalities of North Cotabato, Philippines

Predicting the occurrence of robberies poses significant challenges, requiring valuable data to assist law enforcement personnel in crime prevention and solving efforts. This research paper introduces Crata, a tool that leverages linear regression to predict the robbery frequency in North Cotabato, Philippines. The development of Crata was driven by the analysis of historical data encompassing robbery incidents and inflation rates from 2010 to 2022. The research emphasizes the importance of utilizing the inflation rate as a crucial predictor in determining the robbery frequency. By incorporating this variable into the predictive model, Crata enables more accurate predictions, thus empowering law enforcement agencies with vital insights to address and mitigate crime problems proactively. The robustness and reliability of the tool were assessed through comprehensive evaluations, demonstrating its practical utility and effectiveness. This paper significantly contributes to crime prevention by providing a reliable and data-driven approach to anticipating robberies, enhancing proactive efforts to safeguard the community, and combat crimes. Further research and development are warranted to refine the tool and expand its applicability to other regions for strengthening crime prevention strategies on a broader scale.

A cyclically adjusted spatio-temporal kernel density estimation method for predictive crime hotspot analysis

ABSTRACT This paper presents a new method for predictive crime hotspot analysis that further improves the kernel density estimation (KDE) method and the spatio-temporal kernel density estimation (STKDE) method by accounting for temporal crime cycles and is therefore termed the ‘cyclically adjusted STKDE (cSTKDE) method’. The case study on robbery incidents in Baton Rouge, Louisiana, shows a temporal cycle with a 6-month period of statistical significance from January 2010 to May 2018. This identified period is incorporated into the temporal kernel function of the new cSTKDE method. For validation, the Forecast Accuracy Index (FAI) and Forecast Precision Index (FPI) are used to evaluate the performance across 52 weeks in 2013. For 11 consecutive weeks since the beginning of 2013, the cSTKDE method outperforms the STKDE by 89% lower average abs(1-FAI) and 17% higher average FPI, and outperforms the KDE by 90% lower average abs(1-FAI) and 8% higher average FPI. Overall, the scenario with the best predictive accuracy by the cSTKDE is recommended over the traditional KDE or STKDE method as most feasible and effective in implementation of hotspot policing in practice.

Education- and Income Inequality as Drivers of Violent Property Crime in South Africa: A System Dynamics Model

Crime statistics indicate that the total number of annually reported crimes decreased steadily between 2008 and 2019 in South Africa. However, annually reported robberies have been steadily increasing over the same period. Additionally, South Africa remains plagued by high income inequality. This paper presents a system dynamics simulation model describing the relationships between education inequality, income inequality and robbery in South Africa. The model employs strain theory to project the effectiveness of interventions aimed at increasing South African education levels to decrease income inequality and thereby reduce robbery. The model explored robbery prevention interventions aimed at increasing South African education levels to reduce the current high level of income inequality. The results suggest that reducing robbery incidents through improved education levels will require a long time to become effective but will have long-lasting effects. Furthermore, the results indicate that combinations of interventions generate more substantial effects than the sum of effects produced by interventions applied in isolation.

Reinvestigating the relationship between cities and the spatial distribution of robbery: A tale of eight cities

PurposeThe law of crime concentration suggests cities have almost no impact on the spatial distribution of crime. This study reinvestigates the relationship between cities and the distribution of crime across the various micro-places and neighborhoods which compose these locations. MethodsWe observed robbery incidents reported to police departments across eight U.S. cities from 2015 to 2019. We calculated the spatial variability of the distribution of robberies attributed to census blocks (i.e., micro-places), census tracts (i.e., neighborhoods), and cities (i.e., macro-places) using variance partitioning techniques with multi-level negative binomial regression models. ResultsOur findings are mixed on the relationship between cities and the spatial distribution of robbery incidents. The descriptive analyses suggest a moderate influence of cities on measures of crime concentration. One of our modeling strategies estimates a larger impact while another strategy observes almost no contribution of cities to the total spatial variability. ConclusionsThis study supports previous research which demonstrates there are overwhelming similarities in the distribution of crime between cities and micro-places account for most of the spatial variability of patterns. While cities do not appear to have a major influence on distributions, future research should continue to clarify these mixed findings and provide a more compelling theoretical account of this relationship.

Assault related injury visits in US emergency departments: An analysis by weekday, month and weekday-by-month

ABSTRACT This study investigated the temporal variation (month and day) in assault-related injuries presenting to the US Emergency Departments (ED). An IRB exempt, retrospective review of prospectively collected data was performed using the National Electronic Injury Surveillance System Database from 2005 to 2017 for six categories of assault-related injuries-altercation, sexual assault, robbery, intimate partner violence (IPV), other specified assaults and unknown assault types. National estimates of injuries and associated variables were obtained using SUDAAN software, followed by cosinor analyses for the variation of month and weekday of injury. Three-dimensional topographic representations for weekday-by-month analyses were also created. Over this 13-year time span, there were more than 21 million injury visits due to assault, accounting for 6.57% of all ED visits. While there was no change in the incidence of total number of assaults over the study period, there was a significant increase in the annual percentage incidence of IPV (1.17%; p = .0094) and robbery (2.56%; p = .0001). Cosinor analyses demonstrated a mid-summer peak for all assault types except for robberies (late summer). All assault types showed a weekend peak (late Saturday or early Sunday). Topographical contours exhibited a peak in July and August on early Sunday for all assaults, however the month varied by the type of assault, with weekend peaks in the spring and winter for IPV. This information can be used in prospective resource planning for management and prevention strategies.

Rape as a Rising Traumatic Norm in Nigeria Society: Need for Value Re –Orientation towards Nation Building

There is increase in crime in the Nigerian society today. There is no passing day that incidence of homicide, bandit, arm robbery and rape to mention some are not repeated in various news media. The Nigerian police recorded 717 rape cases between January and May, 2020 (mutual, June 15, 2020). Rape cases have risen to unprecedented height and this Negative trend cannot be tolerated any further in our society, where peace and tranquility is much desired. Without a peaceful and tranquil environment, development of the economy may be truncated. The members of society have been impacted with this stressor called rape. And consequently a number of persons has suffered psychological problems. This condition if not arrested can negatively affect an individual’s economic power, work adjustment and livelihood the researchers perceive the problem of rape are complicated because studies have revealed that it is largely undisclosed by most survivals, under reported by news media and understudied by Researchers. Therefore if no intervention is instituted by way of national value, reorientation of citizens through the educational sector, rape may continue to thrive as a traumatic norm in the Nigeria society, this paper discus bothered on rape as a traumatic norm, disclosure by victim news media and educational intervention through value reorientation. Necessary suggestion are made on how to end this menace in Nigeria.

Https://habibiaislamicus.com/index.php/hirj/article/view/256

The Suri dynasty ruled the subcontinent for a total of 15 years with the four rulers. But this government of the Suri dynasty did not last long as neither the successors of Sher Shah Suri (1540-1545) nor his Pathan emperors who preferred their personal interest over higher interests proved worthy. Sher Shah belonged to the Pathan tribe of "Sur" so he became known in history as Sher Shah Suri. After Sher Shah Suri only his son Islam (Saleem) Shah Suri (1545-1554) succeeded ruled for nine years. Sher Shah Soori established his strong government in a short span of five years. By the time of his death, his government had been established in the entire northern subcontinent. This was no small task but there was a system of government on the basis of which the Mughals established their strong and lasting empire. Sher Shah Soori was a man of military prowess who did many useful things during his reign. As he measured the agricultural land of the whole country and fixed the levies, he improved the road system, and built major roads with four-mile distances, built inns, and planted shady trees. The management of the post office was so good that the news of Bengal reached the king on the third day. In order to improve income, one third of the revenue was taken and it was up to the farmers to decide whether to pay the tax in money or in kind of crop. He enacted a law that in the area where the robbery took place and the robbers were not arrested, all the property they had taken should be brought from the area where the robbery took place. As a result, the incidents of robbery ended. Sher Shah Soori treated Muslim and non-Muslims equally. He gave high positions to the non-Muslims and tried to maintain peace and order in the country. Many non-Muslims studied Persian and got government jobs in northern India like Deccan. Non-Muslims under the Suri era were not despised as foes; but they were given positions of responsibility.

Identifying crime generators and spatially overlapping high‐risk areas through a nonlinear model: A comparison between three cities of the Valencian region (Spain)

The behavior and spatial distribution of crime events can be explained through the characterization of an area in terms of its demography, socioeconomy, and built environment. In particular, recent studies on the incidence of crime in a city have focused on the identification of features of the built environment (specific places or facilities) that may increase crime risk within a certain radius. However, it is hard to identify environmental characteristics that consistently explain crime occurrence across cities and crime types. This article focuses on the assessment of the effect that certain types of places have on the incidence of property crime, robbery, and vandalism in three cities of the Valencian region (Spain): Alicante, Castellon, and Valencia. A nonlinear effects model is used to identify such places and to construct a risk map over the three cities considering the three crime types under research. The results obtained suggest that there are remarkable differences across cities and crime types in terms of the types of places associated with crime outcomes. The identification of high‐risk areas allows verifying that crime is highly concentrated, and also that there is a high level of spatial overlap between the high‐risk areas corresponding to different crime types.

When Crime Moves Where Does It Go? Analyzing the Spatial Correlates of Robbery Incidents Displaced by a Place-based Policing Intervention

Objective: Examine the place-based correlates of robbery activity displaced by a foot-patrol intervention in Newark, NJ. We use constructs from Crime Pattern and Social Disorganization theories to test hypotheses concerned with associations between the structure of the environment and the displacement of crime. Method: Robbery incidents were spatially joined to street segments to study micro-level displacement processes. Predictor variables were operationalized using data from the Newark Police Department and Infogroup USA. Generalized Linear models tested associations between the characteristics of street segments and displaced robbery in the target area as compared to a control. Results: Environmental structure is important to understanding the settings of displacement, though this varied between spatial and temporal displacement. Relationships between displaced crime activity and model covariates did not always appear in expected directions. For example, bus stops predicted increased spatial displacement while corner stores predicted decreased levels of temporal displacement. Conclusions: While testing for displacement has become commonplace in place-based policing interventions, less attention has been paid to the micro-level factors that may facilitate the displacement of crime events. Both bus stops and corner stores show consistent associations with displaced crime activity, but the directions of these relationships suggest more complex processes requiring further examination.

Should Ghana Legalize the Commercial Use of Motor Bikes and Tricycles as Means of Public Transport? A Case Study of Five Selected Regions in Ghana

In the wave of raging debate, even on the floor of parliament, as to whether it would be expedient to commercialize Bikes’ usage in Ghana, it is important to look at its benefits or otherwise. Hence, the study sought to show whether Ghana should legalize the commercial use of motor cycles and tricycles operations. The design was a descriptive study which used quantitative tool to show public acceptance or rejection of commercializing the use of motorcycles and tricycles in Ghana. The study was based on the use of questionnaires for the data collection and were analyzed using Microsoft Excel. The sample population considered was Five (5) Regions in Ghana which are Central, Greater Accra, Bono, Bono East and Northern Regions. Questionnaires of 460 were drawn for the study. It was found out, among others, that many of the riders do not possess licenses; riders are aware of robbery incidents perpetuated by their colleagues; police harassments and passenger pressure are strong reasons for not observing traffic regulations; unfavorable road architecture; the activity is a good source of income. It was therefore recommended that, the okada/pragia/keke/motor king/motor kia operations should be legalized for commercial use with regulations and strict compliance by actors or operators.

Demography and Crime: A Spatial analysis of geographical patterns and risk factors of Crimes in Nigeria

This paper explores the spatial distribution of crime incidences in Nigeria and evaluates the association between the geographical variations and the socio-demographic determinants of crimes. The analyses are based on 2017 reported crime Statistics obtained from the Nigeria‘s National Bureau of Statistics. This paper analysed the spatial patterns of four types of crimes (armed robbery, theft, rape and kidnapping) in relation to their geographical distributions across states in Nigeria. In contrast to the traditional regression analysis, a Poisson mixed model was formulated to incorporate the spatial dependence effects (clustering) and the specific state-level heterogeneity effects of crimes. The study modelled six explanatory variables (unemployment rate, population density, education index, Gross National Income (GNI), percentage males population (PMP), age 18–35 years and policing structure) as the determinants of crimes in Nigeria. A full Bayesian approach via Markov Chain Monte Carlo simulation was used to estimate the model parameters. The results show that the unemployment rate was positively associated with rape, kidnapping and armed robbery, but negatively associated with theft. The results further reveal that GNI and PMP show positive correlation with all the crimes. In addition to the risk factors of the crimes, the proportion variation attributed to clustering effect of the total variation was explained by 29.27 % in armed robbery incidents, 31.30% for theft (stealing), 27.07% for kidnapping and 41.40% in rape cases occurrence. Our approach also produces spatial predictive maps that identified areas of high crime concentration, which can assist the relevant agencies in crimes prevention, effective policing and areas needed urgent attention.

Modeling the risk of robbery in the city of Tshwane, South Africa

ABSTRACT In this study, we model the risk of robbery in the City of Tshwane in South Africa. We use the collective knowledge of two prominent spatial theories of crime (social disorganization theory, and crime pattern theory) to guide the selection of data and employ rudimentary geospatial techniques to create a crude model that identifies the risk of future robbery incidents in the city. The model is validated using actual robbery incidences recorded for the city. Overall the model performs reasonably well with approximately 70% of future robbery incidences accurately identified within a small subset of the overall model. Developing countries such as South Africa are in dire need of crime risk intensity models that are simple, and not data intensive to allocate scarce crime prevention resources in a more optimal fashion. It is anticipated that this model is a first step in this regard.

Schools and neighborhood crime: The effects of dropouts and high-performing schools on juvenile crime

ABSTRACT Most scholars have focused on the simple presence of schools when examining their influence on neighborhood crime. This paper instead examines two school characteristics that might affect local juvenile crime. More specifically, this study uses negative binomial and logistic regression models to estimate the effects of high school dropouts and high-performing schools on juvenile violent crime in Orange County, CA. An integrated theoretical approach based on social bond and routine activity theories is utilized to guide this research. Findings from this study suggest that dropouts are associated with increases in aggravated assault and robbery incidents, but high-performing schools do not significantly affect these crime types. Finally, the models predicting juvenile crime are compared with models predicting all crime (both juveniles and adults), supporting our argument that juvenile crime is the theoretically appropriate crime measure.

Likelihood of Arrest for Robberies, Assaults, and Sexual Offenses Committed by Group and Lone Offenders.

Many criminologists have considered the role of groups in the commission of crime to gain insight into offender decision-making. Additional research is needed, however, that examines the likelihood of arrest as a function of whether an offense is committed by a group of offenders (two or more offenders in a criminal incident) or a lone offender, as well as the number of offenders in the group. Using 3 years of data from the National Incident-Based Reporting System for robbery incidents, assault incidents, and sexual offenses, the study finds that the relative likelihood of arrest for group-offender incidents, compared with lone-offender incidents, varies by incident type. For robbery incidents, the likelihood of arrest increases when committed by a group of offenders. Yet, for assault incidents and sexual offenses, the likelihood of arrest decreases when committed by a group of offenders. Further analysis looks more closely at incidents committed by a group of offenders and how the number of offenders in the group affects the likelihood of arrest. A consistent finding is that for each incident type, the likelihood that all offenders in a group will be arrested is lower as the number of offenders increases, which may justify offenders' perceptions of "safety in larger numbers."

Dissecting the Role of Dominance in Robberies: An Analysis and Implications for Microsociology of Violence.

The influential microsociological theory of violence advanced by Randall Collins suggests that emotional dominance preconditions physical violence. Here, we examine robbery incidents as counterevidence of this proposition. Using 50 video clips of real-life commercial robberies recorded by surveillance cameras, we observed, coded, and analyzed the interpersonal behaviors of offenders and victims in microdetail. We found no support for Collins’s hypothesized link between dominance and violence, but evidence against it instead. It is the absence, not the presence, of emotional offender dominance that promotes offender violence. We consider these results in the light of criminological research on robbery violence and suggest that Collins’s strong situational stance would benefit from a greater appreciation of instrumental motivation and cold-headed premeditation.