Kind Of Crime Research Articles

People accept breaks in the causal chain between crime and punishment.

Crime and punishment are usually connected. An agent intentionally causes harm, other people find out, and they punish the agent in response. We investigated whether people care about the integrity of this causal chain. Across seven experiments, participants (total N = 1,709) rated the acceptability of punishing agents for one crime when the agents had committed a different crime. Overall, participants generally approved of such wayward punishment. They endorsed it more strongly than punishing totally innocent agents, though they often approved of punishing agents for their correct crimes more strongly. Participants sometimes supported wayward punishment when wrongdoers were punished for a different kind of crime than the one committed, and they supported several different kinds of wayward punishments. Together the findings show that people often tolerate breaks in the causal chain between crime and punishment.

Criminological specificity of war crimes, their difference from crimes against humanity and genocide

At the present day sometimes crime of genocide is practically described as a crime against humanity, and the latter is characterized as war crimes. Although some similarity does exist between these kinds of crimes, they have different peculiarities by their constituent elements. These peculiarities possibly may be linked with warfare, but it wouldn’t be correct to bind them entirely with warfare. This difference can be found even in the charters of international criminal tribunals, particularly in various articles of Statute of the International Criminal Court: crime of genocide in Article 6, crimes against humanity in Article 7, and war crimes in Article 8 respectively. Unlike war crimes, crimes against humanity and crime of genocide can be perpetrated both in times of warfare and peace. It’s always important to distinguish the latter from war crimes.

Dynamics of Rural Crime in South Asia: A Criminological Overview

Rural crime in South Asia involves varied and complex issues influenced by various socio-economic, cultural, and political factors of the region. While there are some common types of crime in the rural areas in south Asia, different regions are prone to different kinds of crime. It is because these regions share some common and some unique characteristics. Similarly, there are some shared and unique approaches for addressing the issues related rural crime and ensuring justice. This study, based on a review of existing criminological literature, explores the dynamics of rural crime in the region from a criminological lens. The outcomes of the study will serve the policymakers, law enforcement agencies, and community leaders to address the rural crime and justice issues in the region.

Crime mapping and hot spot analysis using geospatial data in Jalingo metropolis of Taraba State, Nigeria

Crime mapping and hot spot analysis are topical and significant research across the fields of criminology, data digging, city planning and law enforcement for crime control. This study seeks to identify high crime areas which require an officer presence and predicting the possible response demand to increase the efficiency of response officer patrols. Crime type and patterns exist on a spatial level; these patterns and type can be grouped geographically by physical location, and analyzed contextually based on the region in which crime occurs. The study aimed at analyzing crime hotspots using geospatial data in Jalingo metropolis by identifying the different kinds of crime in the study area, determine the spatio-temporal variation of crime occurrences in the study area and determine the high crime density area (hotspot).This study proposed a method to identifying level crime, localize crime hotspots, identify relationship between spatiotemporal crime patterns and social trends, and analyze the resulting data for the purposes of knowledge discovery and anomaly detection. Several types of crime were analyzed in this dataset, including burglary, bribery, forgery ,murder ,rape ,theft drug abuse, assault, and robbery analysis, several interesting findings were drawn about crime in Jalingo metropolis, including: Crime mapping and hotspots with steadily increasing crime levels, hotspots with unstable crime levels, synchronous changes in crime trends throughout Jalingo metropolis as a whole, individual months in which certain hotspots behaved anomalously, and a strong relationship between crime hotspot locations. This type of statistical and correlative analysis of crime patterns will help law enforcement agencies predict criminal activity, allocate resources, and promote community awareness to reduce overall crime rates in Jalingo metropolis. Policing approaches like patrolling and response to crime incidents can be more effective if proper crime mapping and crime hot spot analysis data are available for policing is used to make decisions on crime control in the study area. Predictive policing in crime management use information such as historical crime data to predict crime patterns and response demand. Historical crime data is used to identify high crime areas through kernel density estimation. It is also used to anticipate the levels of response demand. Both of these factors are used to determine how to direct police patrols. This study revealed how kernel density estimation is used for crime mapping and hot spot.

Criminal law counteraction to crimes committed in the form of a credit trap

In recent years, crimes committed in the form of a credit trap have become widespread in China. The so-called credit trap crimes refer to various illegal and criminal actions carried out under the guise of private loans, which seriously violates the financial order and social order of the country, and there is also an increased public danger. Currently, China’s economy is in a transitional stage and the optimization of the business environment is an important part of economic development in the new era, while the stability and prosperity of the private lending market is an important guarantee for the optimization of the business environment. In accordance with the general trend of economic development in the new era, as well as in the context of criminal legislation to maintain financial and social order, the suppression of credit trap crimes and the fight against mafia-criminal forces generated by them are an important task in the round of Special Struggle to eradicate Mafia-criminal Groups. In the context of this Special struggle to eradicate mafia-criminal groups, many problems have arisen in the process of combating the crime of credit trap: firstly, the concept of credit trap is vague, as well as the criteria for the qualification of criminal acts related to credit trap are heterogeneous throughout the country; secondly, the confusion of the concept of the crime credit trap with the concept of usury; thirdly, there was a phenomenon of replacing a certain corpus delicti with the concept of credit trap, it is vague, as well as the criteria for the qualification of criminal acts related to the credit trap are heterogeneous throughout the country; secondly, the confusion of the concept of the crime credit trap with the concept of usury; thirdly, there was a phenomenon of replacing a certain corpus delicti with the concept of credit trap, as well as a court decision has characteristics of a stronger subjectivity, which seriously affects the fairness of justice. Therefore, it is only by clarifying the concept of credit trap and clarifying the criminal illegality of these acts that the crimes of credit trap can be accurately qualified in order to ultimately effectively stop that kind of crime.

An Adaptive Technique for Crime Rate Prediction using Machine Learning Algorithms

Any country must give the investigation and preventive of crime top priority. There are a rising amount of cases that are still pending due to the rapid increase in criminal cases in India and elsewhere. It is proving difficult to classify and address the rising number of criminal cases. Understanding a place's trends in criminal activity is essential to preventing it from occurring. Crime-solving organisations will be more effective if they have a clear awareness of the patterns of criminal behavior that are present in a particular area. Women's safety and protection are of highest importance despite the serious and persistent problem of crime against them. This study offers predictions about the kinds of crimes that might occur in a particular location using ensemble methods. This facilitates the categorization of criminal proceedings and subsequent action in a timely manner. We are applying machine learning methods like KNN, Linear regression, SVM, Lasso, Decision tree and Random forest in order to assess the highest accuracy.

A literature review of the role of forensic linguistics in gender-based violent crimes in Italy

The focus of this article is forensic linguistics as applied to gender-based violence (GBV), a current social problem which persists despite the many measures adopted to eradicate it. Gender-based violence leads to different kinds of crimes, which have been studied from several perspectives such as psychology, criminology and law. In this preliminary study of forensic linguistics applied to GBV crimes in Italy in particular, we aim to provide a review of the research literature on GBV and forensic linguistics. We begin by considering the discipline of forensic linguistics and introducing two psychological models – Walker (1979) and Pence (1993) – which are helpful in contextualising GBV. We then proceed in two directions: first, we examine communication between victims and legal sector professionals; and second, we consider linguistic evidence for police and judicial investigation through discourse analysis of communication between perpetrators and victims. Finally, conclusions are drawn with an eye to future scenarios.

Automatic Face Recognition and Detection for Criminal Identification Using Machine Learning

Abstract: With the use of machine learning technologies, discovering connections and patterns among various types of data has gotten much easier. Finding out what kind of crime might happen given the location where it has previously occurred is the main goal of this research. We have created a model utilizing the machine learning concept using a training set of data that has been cleaned up and transformed. In contemporary civilization, criminal activity is growing dramatically. Effectively identifying criminals to stop crime is the police's principal challenge, but there aren't enough policemen to go around. There are numerous technical approaches to apprehend criminals, yet many of them are ineffective. In this project, a face detection and recognition system for criminal identification is created using a machine learning algorithm. This system will be able to instantly differentiate the 3D faces of criminals and recognize their faces. This system's one-shot learning method only requires a single image of the criminal to identify him. The objective is to identify the criminal from a distance, extract the criminal's information from the database, and notify the police personnel of the location where the criminal was being observed by a camera.

Genesis of Crime and Victim in a Commodity-exchange Society: Theoretical and Empirical Underpinnings of the Rise in Cyber Crimes in India

How is criminality, as a social relation, defined and redefined? Scholars have often explained the same through change in material realities in the political economy. This article attempts to answer the same by premising on Pashukanis’ theory of commodity exchange. He claimed that the definition and progression of criminal liability as a social category resulted from how commodity was exchanged in any particular epoch. It was in the bourgeois epoch that this liability was widened, and this could be possible only after the universalization of the rights-based category—the legal subject. Is this theorization visible, in its materiality, in Sutherland’s comprehension of the white-collar criminal? In the twentieth century, Sutherland, in his work titled ‘White-Collar Crimes’, observed that a novel kind of crime was being committed because of the creation of the middle class in the United States of America. Its victims were the consumers. Is a similar phenomenon visible in twenty-first-century India? What does the universal access to data and greater commission of cybercrimes suggest? This article aims to tie a thread between these three scholars by asking a question—does criminal liability, as a social category and the creation of novel victims, get defined by how the commodity is exchanged in a particular epoch? In other words, this article suggests that the rise of cybercrimes in India should be looked at through the lens of Pashukanis’ commodity-exchange theory.

The spatial association between drugs and urban violence: an analysis for the Metropolitan Region of Recife, Brazil

ABSTRACT The objective of this article is to provide evidence about the association between illegal drugs and urban crimes in Brazil at the neighbourhood level, specifically considering the case of the Recife Metropolitan Region. We apply spatial econometric models to estimate a reliable relationship between drug trafficking and possession and homicide and violent property crimes. The main results indicate strong and robust associations between drug trafficking and both kinds of crimes, but not between drug possession and violent crimes. The set of evidence is obtained even after controlling for the influence of a large set of crime determinants, including not only traditional local socioeconomic conditions affecting violence, but also the presence of slums, employment access, and the presence of bars and restaurants in neighbourhoods.

Highway to the Danger Zone: Spatial Considerations of Catalytic Converter Theft

Limited research exists on catalytic converter theft despite it being a persistent issue for years. This study relies on police data for catalytic converter thefts ( n = 414) in a medium-sized city for 18 months in 2021–2022. The study also uses vehicle registrations in the county, and Census data. Negative binomial regression models use Census Block Groups ( n = 92) and consider neighborhood and environmental characteristics. The most likely vehicles to have catalytic converters stolen are the Honda Element, Toyota Prius, and Ford E-Series van. More than half of thefts occurred in parking garages and parking lots. Regression models find that the most consistent predictor of catalytic converter theft is adjacency to arterial roadways. Results suggest police departments should target efforts at parking garages and lots near highways, close to downtown, in areas that experience other kinds of crime. The situation changes when considering additional neighborhood characteristics, though highways are still a significant predictor.

Mathematical Model for Crimes in Developing Countries with Some Control Strategies

Crime is one among the most challenging problems in most developing countries in which unemployment is among the causes. Not all kind of crimes can be eradicated indeed; this paper is intended to contribute on eradication of unemployment-related crimes in the developing countries by proposing a deterministic mathematical model of unemployment-crime dynamics including vocational training and employment as control measures for crime. The study adopts the epidemiological model concepts on model formulation and model analysis while considering unemployment as main driver of crime. The basic properties of the model are analyzed, and well-posed of the model is established by using the Lipschitz condition. The next-generation matrix is used to obtain the criminal reproduction number which help to derive the conditions for local and global stability of the model. Moreover, the existence of backward and forward bifurcation when the crime reproduction number is equal to one was analyzed by center manifold theory. Simulations of the model are carried out to validate the theoretical part of the model and demonstrate vocational training, and employment strategies are more effective in combating crime when applied simultaneously. The findings suggest that unemployment problem should be addressed in order to reduce the number of unemployed individuals in joining the criminal activities.

Terrorist and extremist crimes among young people and regionally sensitive prevention

Preventing extremism and terrorism crimes in the republics of the North Caucasus in the near future is relevant, since today’s volatile situation in society calls for constant reference to the problem in order to comprehend the development of these crimes in the face of the liberalization of public life. Evaluating regional and territorial characteristics of crime suggests that its content depends not only on the state of society at large, but also on the way social processes are organized in the regions. Therefore, there are some significant differences in the level of terrorism and extremism crime among young people in different regions of the Russian Federation. In this sense, the nature and rate of crime in the border regions are relatively localized within regional-territorial frameworks. This is due to the factthat, some regions of the Russian Federation have developed peculiar demographic, cultural, socio-economic, geopolitical conditions that affect the qualitative and quantitative indicators of youth crime, causing peculiar criminological situations to develop in certain regions. Regional analysis of crime is a mandatory attribute of criminological research. Within its framework, terrorism and extremism crime among young people is considered as an integrative output of complex social territory-specific interactions. Attempts to feature terrorism and extremism crime among young people in the republics of the North Caucasus, the way it differs from this kind of crime in other regions of the Russian Federation are of great preventive importance.

SUBJECTIVE SIGNS OF LEGALIZATION OF REVENUE RECEIVED FROM CRIMINAL ACTIVITIES

The article analyzes the general concept of money laundering. All over the world, the international community, including the United Nations, recognizes the legalization of proceeds from crime as one of the most widespread and dangerous transnational crimes. The growing danger of the legalization of criminal proceeds in the modern world is of concern to the vast majority of countries in the world community. According to experts, “in recent years, the proceeds from various kinds of crimes in the field of money laundering have been from 2 to 5% of the total world gross product, that is, from 1 to 3 trillion US dollars”. With the globalization of the world financial system, the question arises of the need to coordinate the efforts of states to combat money laundering at the international level. In the world, special importance is attached to the fight against crime, the imposition of sentences by the courts for crimes committed in accordance with the principle of justice, and the liberalization of criminal legislation. Thus, special attention is paid to conducting research in the field of determining responsibility for the legalization of proceeds from crime and preventing the causes and conditions that contribute to its occurrence, the correct qualification of this crime, and strengthening the implementation of international standards in this area in national legislation

The Challenges of the Digital Age: The Problems of Criminal Liability for Cybercrimes in Lithuanian Law

Abstract The spread of digital technology and the convergence of computer and communication devices have changed the way people communicate, do important jobs, and so on. However, this digital age has also opened up a wide range of possibilities of using computer technology for criminal purposes. Therefore, the purpose of this research paper is to specify the main problems of legal regulation and case law of criminal liability for cybercrimes in Lithuanian law. So, the analysis was based on three main questions: the difficulties in legal regulation of cybercrimes in Lithuanian criminal law; the problematic relation between cybercrimes and other related crimes as well as the problems of applying some composition features of cybercrimes in Lithuanian case law. The research was carried out by employing the logical, the systematic, the linguistic, the historical, the comparative and the synthesizing research methods as well as the analysis of legal documents. The analysis shows that the legal regulation of criminal liability for cybercrimes in Lithuanian law has considerable problematics compared to international standards, as well as some composition features of cybercrimes are inappropriate for their application in practice and there many problems with ratio between this kind of crimes and similar crimes in Lithuanian case law.

Retinopathy Image Augmentation Using Robust Generative Adversarial Networks (GANs) : A Review

Crimes against women have become a global problem, and many governments are striving to curb them. The National Crime Records Bureau indicates that crimes against women have risen substantially. In June, NCW received the most crime complaints against women in eight months. The Indian government is interested in finding a solution to this problem and promoting social progress. Each year, crime reports generate a vast amount of data, which is collated. This information may help us evaluate and anticipate criminal behavior and reduce criminal activity. Data analysis involves assessing, cleansing, manipulating, and modelling data to draw conclusions and enhance decision-making. This research uses supervision learning to analyze the Indian women's criminal examination. The police department received crime reports. Anomalies, invalid locations, longitudes, and scopes were created in advance. The study was meant to breakdown women's crimes by kind and district and produce crime heat maps. The results help decision makers predict and prevent crimes against women. Applying Find the geographical criminal hotspot and the kind of crime, such as murder, rape, sexual assault, beating, dowry threats by the husband or his family, immoral trafficking, stalking, etc.

A Review on Forecasting Crime against women in India using Machine Learning Approaches

Crimes against women have become a global problem, and many governments are striving to curb them. The National Crime Records Bureau indicates that crimes against women have risen substantially. In June, NCW received the most crime complaints against women in eight months. The Indian government is interested in finding a solution to this problem and promoting social progress. Each year, crime reports generate a vast amount of data, which is collated. This information may help us evaluate and anticipate criminal behavior and reduce criminal activity. Data analysis involves assessing, cleansing, manipulating, and modelling data to draw conclusions and enhance decision-making. This research uses supervision learning to analyze the Indian women's criminal examination. The police department received crime reports. Anomalies, invalid locations, longitudes, and scopes were created in advance. The study was meant to breakdown women's crimes by kind and district and produce crime heat maps. The results help decision makers predict and prevent crimes against women. Applying Find the geographical criminal hotspot and the kind of crime, such as murder, rape, sexual assault, beating, dowry threats by the husband or his family, immoral trafficking, stalking, etc.

Sociodemographic and psycho social Differences Between Hate Crime Offenders and Other Non-Bias-Motivated Criminals: Implications for Prison Rehabilitation Programs.

Hate crimes have severe consequences for the victims and for all members of the victim's social category. Prison programs must address the criminogenic needs of the participants, especially in this kind of crime, in order to prevent recidivism. This study seeks to understand the role of prejudice and aggression in the execution of hate crimes, in order to design effective interventions for hate crime offenders. Sociodemographic, criminological, and psychosocial variables were assessed in a sample of 33 hate crime offenders sentenced to prison or community service and in a group of 38 non-bias-motivated criminals (n = 71). The individuals convicted of hate crimes have higher reactive and proactive aggression, subtle prejudice, homophobia, and social dominance orientation. The implications of these results for the Penitentiary Administration programs will be discussed.

A Review on the Mechanism Mitigating and Eliminating Internet Crimes using Modern Technologies

There is no doubting that contemporary technology creates new hazards, and these threats are many and significant, directly harming people's lives and threatening their stability. Because of the increased use of computers and Internet-connected cellphones in recent years, the problem of cybercrime has expanded substantially. Unquestionably, this kind of crime is now a reality that jeopardizes people's reputations and lives, therefore we must be aware of it to prevent being a victim. The exponential growth in internet connectedness is closely tied to a rise in cyberattack incidences, frequently with significant consequences. Malware is the weapon of choice for carrying out malicious intent in cyberspace, whether by exploiting pre-existing flaws or exploiting the unique properties of new technology. There is an urgent need in the cybersecurity area to develop more inventive and effective virus defense techniques. To do this, we first give an overview of the most often exploited vulnerabilities in the current hardware, software, and network layers. This follows criticism of the most recent mitigation efforts and the reasons why they may or may not be helpful. Following that, We'll talk about new attack methods for cutting-edge technologies including social networking, cloud computing, mobile technology, as well as critical infrastructure. We conclude by sharing our speculative findings on potential future research avenues.

THE INJUSTICE OF UNDER-POLICING IN AMERICA

THE INJUSTICE OF UNDER-POLICING IN AMERICA