Institutions and the Growth of Knowledge: Evidence from International Environmental Regimes

This article argues that institutions not only reflect ideas prevalent at the time of their creation, but also play vital roles in driving the growth and dissemination of knowledge. Because institutions are not actors in their own right, however, it is essential to identify the mechanisms through which they influence the behavior of those who are producers and consumers of knowledge. The central section of the article explores three distinct mechanisms or families of mechanisms that come into play in this context:(1) framing the research agenda, (2) privileging certain types of knowledge claims, and (3) guiding the application of knowledge to specific policy concerns. The article's concluding section examines the policy implications flowing from the proposition that institutions play significant roles in creating knowledge regarding the issues they address. Throughout, observations relating to international environmental or resources regimes provide a source of illustrations.     

Dispositional Sensitivity to Befallen Injustice

Dispositional Sensitivity to Befallen Injustice (SBI) is proposed as a new construct. A self-report questionnaire with four types of indicators (frequency, intensity of anger, intrusiveness of thoughts, punitivity) was developed for measuring SBI. Using structural equation modeling and the general rationale of multitrait-multimethod analysis, the convergent and discriminant validity of this questionnaire was investigated vis-à-vis measures for Trait Anger, Anger In, Anger Out, and Frustration Tolerance as related constructs. Additionally, a meaningful pattern of correlations was obtained between SBI and Life Satisfaction, Centrality of Justice, Interpersonal Trust, and Need for Control. Finally, self-reported sensitivity to befallen injustice was found to predict cognitive, emotional, and behavioral reactions to unjust treatment in laboratory and natural settings several weeks later.     

结构方程模型在社会工作研究中的应用初探

社会工作研究中要注重定性研究和定量研究的互相补充与支持。结构方程模型(StructuralEquationModeling,SEM)是在已有的理论基础上,用与之相应的线性方程系统表示该理论的一种多变量统计分析方法,又称协方差结构分析(CovarianceStructureAnalysis)因果模型(CausalModeling)。在社会工作的研究中,应用结构方程模型要有一定的标准和条件。     

FAMILY MATTERS: EFFECTS OF FAMILY MEMBERS’ RESIDENTIAL AREAS ON CRIME LOCATION CHOICE*

According to crime pattern theory, offenders are likely to select crime locations within their awareness space. Previous studies have shown that offenders often commit crimes within their current and former residential areas and in areas they previously targeted. However, offenders’ awareness spaces obviously consist of more locations that potentially influence their crime location choices. This study examines the importance of the residential areas of offenders’ family members. Most offenders visit their families at least occasionally and consequently get familiar with the areas in which their families live. It is hypothesized that family members’ residential areas are at increased risk of being targeted. Unique data were used to reconstruct residential histories of the parents, siblings, and children of 7,910 offenders who committed 19,420 offenses. The results of discrete spatial choice models showed that residential areas of family members are indeed at increased risk of being targeted. Current familial residential areas had stronger and more consistent effects than had former familial residential areas. Effects were strongest for the residential areas of offenders’ children compared with those of their parents and siblings. The residential areas of male and female family members affected the crime location choices of male and female offenders equally.     

因果观念发展的大数据相关关系观照

随着人类认识的深化和实践活动层次的提升,人类因果观念经历了两次重要转换,形成了三种基本的因果观:实在论因果观、描述论因果观和模型论因果观。从实在论因果观到描述论因果观,肇因于从经典物理学到量子力学的发展;从描述论因果观到模型论因果观,则源自信息科技特别是大数据的发展。在三种因果观念中,实在论因果观是关于对象确定性联系的把握,描述论的因果观是将实在论因果观抽象为描述的产物,而模型论因果观则是描述论因果观发展到完全抽离具体经验条件的结果。纵观人类认识发展过程中因果观的嬗变,可以进一步看到,因果观念的两大重要转换都与信息的彰显密切相关。在量子力学中,信息便得以空前凸显,微观观测中生成的量子现象正是作为感受性关系的信息;而大数据则本身就是信息数字编码的产物,正是大数据相关关系,将因果观念从主要基于物能发展到主要基于信息。     

Analyzing Criminal Trajectory Profiles: Bridging Multilevel and Group-based Approaches Using Growth Mixture Modeling

Over the last 25 years, a life-course perspective on criminal behavior has assumed increasing prominence in the literature. This theoretical development has been accompanied by changes in the statistical models used to analyze criminological data. There are two main statistical modeling techniques currently used to model longitudinal data. These are growth curve models and latent class growth models, also known as group-based trajectory models. Using the well known Cambridge data and the Philadelphia cohort study, this article compares the two “classical” models—conventional growth curve model and group-based trajectory models. In addition, two growth mixture models are introduced that bridge the gap between conventional growth models and group-based trajectory models. For the Cambridge data, the different mixture models yield quite consistent inferences regarding the nature of the underlying trajectories of convictions. For the Philadelphia cohort study, the statistical indicators give stronger guidance on relative model fit. The main goals of this article are to contribute to the discussion about different modeling techniques for analyzing data from a life-course perspective and to provide a concrete step-by-step illustration of such an analysis and model checking.

Contrasting simulated and empirical experiments in crime prevention

This paper argues that simulated experiments of crime prevention interventions are an important class of research methods that compare favorably with empirical experiments. It draws on Popper’s demarcation between science and non-science (Conjectures and refutations: the growth of scientific knowledge. Routledge, London, 1992) and Epstein’s principle of generative explanation (Generative social science: studies in agent-based computational modeling. Princeton University Press, Princeton, NJ, 2006) to show how simulated experiments can falsify theory. The paper compares simulated and empirical experiments and shows that simulations have strengths that empirical methods lack, but they also have important relative weaknesses. We identify three threats to internal validity and two forms of external validity peculiar to simulated experiments. The paper also looks at the problem of validating simulations with crime data and suggests that simulations need to mimic the error production processes involved in the creation of empirical data. It concludes by listing ways simulations can be used to improve empirical experiments and discussing the differing operating assumption of empirical and simulation experimentalists.

Preparation of Tool Mark Standards with Jewelry Modeling Waxes

Abstract:  This paper presents how jewelry modeling waxes are used in the preparation of tool mark standards from exemplar tools. We have previously found that jewelry modeling waxes are ideal for preparing test tool marks from exemplar tools. In this study, simple methods and techniques are offered for the replication of accurate, highly detailed tool mark standards with jewelry modeling waxes. The techniques described here demonstrate the conditioning and proper use of jewelry modeling wax in the production of tool mark standards. The application of each test tool's working surface to a piece of the appropriate wax in a manner consistent with the tool's design is clearly illustrated. The resulting tool mark standards are exact, highly detailed, 1:1, negative impressions of the exemplar tool's working surface. These wax models have a long shelf life and are suitable for use in microscopic examination comparison of questioned and known tool marks.     

CAN HOT SPOTS POLICING REDUCE CRIME IN URBAN AREAS? AN AGENT‐BASED SIMULATION*

Over the past two decades, there has been a growing consensus among researchers that hot spots policing is an effective strategy to prevent crime. Although strong evidence exists that hot spots policing will reduce crime at hot spots without immediate spatial displacement, we know little about its possible jurisdictional or large‐area impacts. We cannot isolate such effects in previous experiments because they (appropriately) compare treatment and control hot spots within large urban communities, thus, confounding estimates of area‐wide impacts. An agent‐based model is used to estimate area‐wide impacts of hot spots policing on street robbery. We test two implementations of hot spots policing (representing different levels of resource allocation) in a simulated borough of a city, and we compare them with two control conditions, one model with constant random patrol and another with no police officers. Our models estimate the short‐ and long‐term impacts on large‐area robbery levels of these different schemes of policing resources. These experiments reveal statistically significant effects for hot spots policing beyond both a random patrol model and a landscape without police. These simulations suggest that wider application of hot spots policing can have significant impacts on overall levels of crime in urban areas.     

How federalism influences welfare spending: Belgium federalism reform through the perspective of the synthetic control method

The question of whether and how federalism influences a country's welfare state has been a longstanding concern of political scientists. However, no agreement exists on exactly how, and under what conditions, federal structures impact the welfare state. This article examines this controversy. It concludes theoretically that the specific constellation of federal structures and distribution of powers need to be considered when theorising the effects of federalism on the welfare state. Using the case of Belgium and applying the synthetic control method, it is shown in the article that without the federalism reform of 1993, the country would have had further decreases in social spending rather than a consolidation of this spending in the years after 1993. In the case of Belgium, the combination of increased subnational spending autonomy in a still national financing system provided ideal conditions for a positive federalism effect on social spending to occur.