Reimagining Sutherland 80 years after white‐collar crime*

Eighty years ago, Edwin H. Sutherland conceptualized and defined white‐collar crime. In this article, I engage retrospectively with Sutherland's ideas and work to emphasize important aspects that continue to guide research today; to note where he was prescient as well as shortsighted. I center this discussion around “corporate crime” or crimes by business. Four main themes are discussed: 1) law and official responses to corporate offending—the data problem, 2) corporate crime and the life cycle of organizations, 3) psychological and trait‐based explanations, and 4) consequences of definitional ambiguity.     

Comparing crime reporting factors in EU countries

Through crime-reporting citizens make their security needs explicit to the police. This information helps the police in the allocation of resources. In the European Union, there are significant differences among countries, both in terms of overall and specific crime-reporting rates. Factors highlighted by the literature that might explain these differences are not entirely satisfactory. There is little comparative research, and most published studies are nation-centred, based on the experience of central and northern European countries, and largely focused on the situational variables related to the criminal incident itself. It is widely assumed that situational variables have a universal explanatory capacity in crime reporting. This article questions this assumption and shows that a number of factors weight differently in explaining national rates. Following a literature review, we identified four groups of causal factors and analysed their explanatory capacity. These are related largely to the incident (rational models) and victims’ perception (psychological models). In addition, we also analysed the influence of institutional and community factors. The European Survey on Crime and Safety database was used for our analysis. Results show the existence of two areas in Europe, the north-central area and the south-eastern area, in terms of crime reporting rates and the factors that explain these differences. Rational and psychological models explain crime-reporting practices better in the north-central area. In contrast, socio-demographic variables and social inequalities are more relevant for explaining crime reporting in the south-eastern area of Europe. Institutional variables are also important in eastern countries. Community factors are not significant explanatory variables due to the limitations of indicators available in the database. Our research reveals that crime-reporting is a rather more complex phenomenon than is often assumed, and highlights the limitations of existing knowledge and methodologies on comparative crime-reporting.     

Robust Shoeprint Retrieval Method Based on Local‐to‐Global Feature Matching for Real Crime Scenes

In this study, an automatic and robust crime scene shoeprint retrieval method is proposed. As most shoeprints left at crime scenes are randomly partial and noisy, crime scene shoeprint retrieval is a challenging task. To handle partial, noisy shoeprint images, we employ denoising deep belief network (DBN) to extract local features and use spatial pyramid matching (SPM) to obtain a local‐to‐global matching score. In this study, 536 query shoeprint images from crime scenes and a large scale database containing 34,768 shoeprint images are used to evaluate the retrieval performance. Experimental results show that the proposed method outperforms other state‐of‐the‐art methods in terms of retrieval accuracy, feature dimension, and retrieval speed. The proposed method achieves a cumulative match score (CMS) of 65.67% at top 10 which is 5.60% higher than the second best performing method.     

Drugs and crime revisited

The relationship between drugs and crime is investigated, building on previous research by Huizinga, Menard, and Elliott and by Goldstein and his colleagues. The previous research is extended by examining the relationship between drugs and crime at different stages of the life course, adolescence and early adulthood; by extending the age range used in previous research by Huizinga and colleagues; and by examining the impact of adolescent substance use and illegal behavior on adult substance use and illegal behavior. The results are consistent with past research in finding that (1) for initiation, the “drug use causes crime” hypothesis is untenable because crime typically is initiated before substance use; (2) more serious forms of crime and substance use usually are initiated after minor forms of those behaviors, and rarely in the absence of such behaviors; and (3) once crime and substance use are initiated, each appears to increase the likelihood of continuity of the other or (equivalently) to reduce the likelihood of suspension. Beyond results from prior research, it also appears that (4) crime and drug use are more closely related in adolescence than in adulthood, and that (5) examination of the transition from adolescence to adulthood suggests that the most plausible conclusion is that drugs and crime are related by mutual causation: crime affects drug use and drug use affects crime.     

Prison population growth and crime reduction

The impact of state prison populations on crime is typically estimated by applying the lambda, the individual crime rate, of prisoners or arrestees. We outline the problems with this approach, attempt to reanalyze the widely divergent lambdas derived in past research, and make adjustments necessary to use lambdas for estimating the incapacitation impact. The result is an uncertain estimate of 16 to 25 index crimes averted per year per each additional prisoner. We argue that regression analysis can provide a better estimate of the impact of prison population growth. Applying the Granger test to pooled state data over 19 years, we found that prison population growth leads to lower crime rates but that crime rate changes have little or no short-term impact on prison population growth. Next we regressed crime rates on prison population and conclude that, on average, at least 17 index crimes are averted per additional prisoner. The impact is limited mainly to property crime.     

Re-imagining crime prevention: controlling corporate crime?

While the discourses and practices of crime prevention are of increasing salience, few criminologists have sought the inclusion of corporate illegalities on such agendas. Relatedly, within criminology, there has been a diminished tendency to think in idealistic, utopian and emancipatory terms. This paper is one small attempt to think in precisely such terms.¹ But it is not an exercise in pure imagination. In particular, the paper makes extended reference to Finland, where recent experience suggests that corporate crime prevention may be feasible, under certain conditions, albeit subject to certain limitations. Thus we consider both the desirability and the feasibility of corporate crime prevention intruding upon the generally narrowly constructed terrain of ‘crime prevention’. We begin with a critique of some of the key aspects of crime prevention discourses – at both theoretical and practical levels – with a particular emphasis upon the extent to which these are both more appropriately and usefully applied to corporate crime prevention, before going on to discuss corporate crime prevention ‘in action’, through a focus upon recent developments in Finland. In a concluding section, we consider various aspects of both the desirability and feasibility of corporate crime prevention.     

Hate groups and hate crime

This paper is the first to investigate the relationship between hate groups and hate crime empirically. We do so using panel data for the U.S. states between 2002 and 2008. Contrary to conventional wisdom, we find little evidence that hate groups are associated with hate crime in the United States. We find somewhat stronger evidence that economic hardship may be related to hate crime. However, evidence for the potential importance of economic factors remains weak. Further, we find that demographic variables are not significantly related to hate crime in the United States. Our results leave the question of what factors may drive hate crime in America unresolved. But they cast doubt on the popular perception that hate groups are among them.     

Anticipating organized and transnational crime

This paper seeks to identify ways in which governments and lawenforcement agencies might enhance the effectiveness of their efforts toanticipate organized crime. It starts by defining what is meant byanticipation, and differentiating it from the much more difficult task ofprediction. The analysis then identifies some of the methods and modelsthat are generally accepted as part of the existing knowledge base onorganized crime and highlights how these can be used to anticipate futuredevelopments and to develop warnings about how criminal organizationsmight evolve and behave in the future. The knowledge base includespolitical, economic, sociological, strategic, and composite models and showshow they provide a foundation for anticipating future developments inorganized crime. The models are either models about the kind ofenvironment in which organized crime flourishes or models about the waysin which organized crime behaves. What we do, in effect, is to identifyand elucidate `models' in ways that provide propositions about the kindsof developments, innovations or changes we might see in organized crime(both domestic and transnational) in the future. Underlying indicators provide warning about future manifestations of organized crime. Anticipating these manifestations provides a basis for appropriatepreventive, defensive or mitigating strategies. Finally, the article providessome examples of specific techniques of information collection andintelligence analysis that might assist in this task of anticipation.     

Forensic determination of hair deposition time in crime scenes using electron paramagnetic resonance

Several types of biological samples, including hair strands, are found at crime scenes. Apart from the identification of the value and the contributor of the probative evidence, it is important to prove that the time of shedding of hair belonging to a suspect or victim matches the crime window. To this end, to estimate the ex vivo aging of hair, we evaluated time‐dependent changes in melanin‐derived free radicals in blond, brown, and black hairs by using electron paramagnetic resonance spectroscopy (EPR). Hair strands aged under controlled conditions (humidity 40%, temperature 20–22°C, indirect light, with 12/12 hour of light/darkness cycles) showed a time‐dependent decay of melanin‐derived radicals. The half‐life of eumelanin‐derived radicals in hair under our experimental settings was estimated at 22 ± 2 days whereas that of pheomelanin was about 2 days suggesting better stabilization of unpaired electrons by eumelanin. Taken together, this study provides a reference for future forensic studies on determination of degradation of shed hair in a crime scene by following eumelanin radicals by utilizing the non‐invasive, non‐destructive, and highly specific EPR technique.     

Race,ethnicity, and social change: The democratization of middle‐class crime*

Since the mid‐1970s, the percentage of non‐White people convicted of white‐collar type crimes in the federal judicial system has been growing steadily. In 2015, non‐Whites accounted for more than half of all convictions for certain white‐collar type crimes, but the increase in non‐White participation has not occurred evenly across all race and ethnic groups. Asians and Latinos have increased their participation in white‐collar crime more so than Blacks. Using data from the U.S. Sentencing Commission, the Equal Employment Opportunity Commission, and the U.S. Census, we investigate whether the differential increase among race and ethnic groups in white‐collar type crimes can be explained by their differential increase in middle‐class occupations. The findings have implications for opportunity, cultural, and race‐centered perspectives on crime, as well as institutional anomie theory, and they suggest that low‐level white‐collar crimes are being democratized along lines of race and ethnicity.     

Do crime hot spots affect housing prices?

ABSTRACT

Our knowledge about what happens to housing values when properties are close to places with high concentrations of crime, often called ‘hot spots’, is limited. Previous research suggests that crime depresses property prices overall, but crime hot spots affect house prices more than crime occurrence does and may affect prices of single-family houses more than prices of flats. Here we employ hedonic price modelling to estimate the impact of crime hot spots on housing sales, controlling for property, neighbourhood and city characteristics in the Stockholm metropolitan region, Sweden. Using a Geographic Information System (GIS), we combine property sales by coordinates into a single database with locations of crime hot spots. The overall effect on house prices of crime (measured as crime rates) is relatively small, but if its impact is measured by distance to a crime hot spot, the effect is non-negligible. By moving a house 1 km further away from a crime hot spot, its value increases by more than SEK 30,000 (about EUR 2,797). Vandalism is the type of crime that most affects prices for both multi- and single-family housing, but that effect decreases with distance from a crime hot spot.     

Differential social organization, collective action, and crime

This article elaborates and extends Sutherland’s [Principles of criminology (4th ed.), Lippincott, Philadelphia, Sutherland (1947)] concept of differential social organization, the sociological counterpart to his social psychological theory of differential association. Differential social organization contains a static structural component, which explains crime rates across groups, as well as a dynamic collective action component, which explains changes in crime rates over time. I argue that by drawing on George Herbert Mead’s [Mind, self, and society. University of Chicago Press, Chicago, Mead (1934)] theories of symbolic interaction and social control, we can conceptualize organization in favor of, and against, crime as collective behavior. We can then integrate theoretical mechanisms of models of collective behavior, including social network ties, collective action frames, and threshold models of collective action. I illustrate the integrated theory using examples of social movements against crime, neighborhood collective efficacy, and the code of the street. A portion of this chapter was presented at the Annual Meetings of the American Society of Criminology, Toronto, Canada, November 16–19. The research upon which this paper was based was supported in part by grants from the National Science Foundation (SES-0004323) and the National Institute on Drug Abuse (R01DA18148). The funding agencies bear no responsibility for the analyses and interpretations drawn here. James F. Short, Jr. and Joachim Savelsberg generously provided comments on an earlier draft.     

Perceived crime seriousness: Consensus and disparity

In this article, the statistical technique for setting up the consensus of perceived crime seriousness in previous studies is critically reviewed. The conventional method, when applied to a data set of crime seriousness, is found to have exaggerated the consensus because, by using a more appropriate model, which assumes perfect agreement in crime severity between subgroups, the consensus is reduced unanimously. By breaking down the population by gender, age, and educational level, sociodemographic differentials in crime seriousness are set up. The disparity is then further examined in details by paired comparisons between a target crime with fourteen other crimes. The three factors are all found to be important in affecting perceived crime seriousness. This conclusion is different from that of previous studies. The scaling method is found to be responsible for the difference. As the Thurstone method used in this study is more responsive and can produce more discriminating results, it is recommended for future research in crime severity. Finally, the implications of the findings on some important issues, like the appropriateness of legal penalty and the construction of a crime index, are discussed.     

Explaining Korean women's fear of crime

This study is intended to explain the fear of crime among Korean women. Due to the complexity of concept and measurement of fear, this study was designed to measure specific or concrete fear and general or formless fear. Data were obtained from a self‐administered survey to 528 Korean women living in the city of Seoul, Korea. The results revealed that the fear of crime seems to be experienced differently. That is, specific fear appears to be most influenced by their knowledge of the occurrence of crime, followed by community environment and their perceptions about the incidence of crime, while the general fear of crime seems to be explained only by their perceptions about the incidence of crime at the significance level of p<.05.     

Using Bayes’ theorem in behavioural crime linking of serial homicide

Purpose. The study extends research by Santtila et al. (2008) by investigating the effectiveness of linking cases of serial homicide using behavioural patterns of offenders, analysed through Bayesian reasoning. The study also investigates the informative value of individual behavioural variables in the linking process. Methods. Offender behaviour was coded from official documents relating to 116 solved homicide cases belonging to 19 separate series. The basis of the linkage analyses was 92 behaviours coded as present or absent in the case based on investigator observations on the crime scene. We developed a Bayesian method for linking crime cases and judged its accuracy using cross‐validation. We explored the information added by individual behavioural variables, first, by testing if the variable represented purely noise with respect to classification, and second, by excluding variables from the original model, one by one, by choosing the behaviour that had the smallest effect on classification accuracy. Results. The model achieved a classification accuracy of 83.6% whereas chance expectancy was 5.3%. In simulated scenarios of only one and two known cases in a series, the accuracy was 59.0 and 69.2%, respectively. No behavioural variable represented pure noise but the same level of accuracy was achieved by analysing a set of 15, as analysing all 92 variables. Conclusion. The study illustrates the utility of analysing individual behavioural variables through Bayesian reasoning for crime linking. Feasible applied use of the approach is illustrated by the effectiveness of analysing a small set of carefully chosen variables.     

Transnational white-collar crime and risk

Research Summary Business transactions have increasingly been crossing national borders, thereby presenting greater opportunities for white-collar crime and for the externalization of risk. The global economic crisis, resulting in part from the subprime mortgage scandal, is a prime example of this potential. To develop theoretical perspectives and practical interventions to prevent and respond to the global financial crisis, we consider similar issues of risk and white-collar crime associated with global transactions in electronic waste (E-waste). Policy Implications Smart (or responsive) regulation is a promising approach for addressing both E-waste and the current economic crisis. This response includes crime prevention, third-party- and self-regulation, and the threat of strong state intervention. Future research should explore the extent to which smart regulation reduces specific forms of white-collar crime and risk, as well as whether these interventions generalize to other transnational problems.     

Towards rational and evidence-based crime policy

Rational crime policy constitutes a basic goal for society. If, however, evidence-based, cost-efficient crime prevention is the standard, there is little indication that current policies—including programs, laws, and court decisions—are rational. To support that assessment, this article uses an evaluation research perspective to highlight five prominent problems with extant crime policies: (1) a lack of empirical assessment of the need for them; (2) a range of design issues, including gaps between crime theory and policy, and, most notably, the pursuit of silver bullet solutions; (3) a range of implementation issues, including disjunctures between ideal and actual practice; (4) the lack of rigorous impact evaluations and the sometimes misplaced emphasis on them; and (5) a scarcity of cost-efficiency analyses for guiding investment decisions. It then discusses the implications of these problems and suggests steps that can be taken to place crime policy on a more evidence-based foundation.     

Personal networks and crime victimization among Swedish youth

We combine routine activity theory, lifestyle-victimization theory, and a social network perspective to examine crime victimization. In particular, we study to what extent crime victimization is associated with having close contacts who have been victimized and/or who engage in risky lifestyles. We use the data (collected in 2014) of 1,051 native Swedes and 1,108 Iranian and Yugoslavian first- or second-generation immigrants in Sweden who were all born in 1990. They were asked to describe their personal characteristics, various behaviours, and past personal experiences with crime victimization, as well as those of the five persons with whom they most often spend their leisure time. Our findings support the network perspective: crime victimization is negatively associated with the number of close contacts an individual mentions but is substantially more likely for those who have many close contacts who have themselves been victimized. In terms of a risky lifestyle that may enhance the likelihood of being victimized, we found only that individuals who get drunk frequently were at somewhat higher risk of being victimized. To guard young individuals against crime victimization, it might thus be worthwhile to focus more on with whom they associate than on their potentially risky lifestyles or attitudes.     

Mobsters are human too: Behavioural science and organized crime investigation

The paper describes the organized criminal, and the fight against organized crime from a behavioural point of viiew. The author considers the organized criminal a crime-entrepreneur who has to operate in an enduring violent entrepreneurial landscape in which he has to cope with the problem of social information management. The article described how the police can add a social psychological approach to the traditional investgative methods. I provides some experience obtained in the Netherlands in which the psychologist assisted the crime squad during the investigation, trial preparation and trial. It argues in favour of a more analytical, hypothesis testing method in whch the behavioural scientist is integrated in the operational organized crimesquad instead of acting as an outside consultant.