Conclusions

The prevention of atrocity crimes is the cornerstone of R2P. Yet, how prevention works in practice is little understood. In practice, multiple actors at different levels employ multiple prevention tools simultaneously which relate to, and impact upon, the regional, national and local contexts in which atrocity crime risk is evident. Strengthening preventive action requires better understanding of the combination of measures employed and how these measures interact and affect the risk of atrocity crimes. Recognising the growing gap between the promise and practice of atrocity prevention, the UN Office on Genocide Prevention and R2P commissioned a series of case studies to evaluate atrocity prevention efforts, covering the countries of Burundi, Central African Republic, Cote d’Ivoire, Guinea, Kenya, Myanmar, South Sudan and Syria. From these studies, four main lessons become apparent. One, imminently apprehended atrocity crimes are preventable. Two, best outcomes are achieved when atrocity prevention is made a priority. Three, unity of purpose is essential. And four, atrocity prevention relies on several factors, some of which are outside the control of those undertaking prevention. These lessons mean that while atrocity prevention is difficult, it is possible.

Understanding the Spatiotemporal Pattern of Crimes in Changchun, China: A Bayesian Modeling Approach

Chinese cities have been undergoing extraordinary changes in many respects during the process of urbanization, which has caused crime patterns to evolve accordingly. This research applies a Bayesian spatiotemporal model to explore and understand the spatiotemporal patterns of crime risk from 2008 to 2017 in Changchun, China. The overall temporal trend of crime risk, the effects of land use covariates, spatial random effects, and area-specific differential trends are estimated through a Bayesian spatiotemporal model fitted using the Integrated Nested Laplace Approximation (INLA). The analytical results show that the regression coefficient for the overall temporal trend of crime risk changed from significantly positive to negative after the land use variables are incorporated into the Bayesian spatiotemporal model. The covariates of road density, commercial and recreational land per capita, residential land per capita, and industrial land per capita are found to be significantly associated with crime risk, which relates to classic theories in environmental criminology. In addition, some areas still exhibit significantly increasing crime risks compared with the general trend even after controlling for the land use covariates and the spatial random effects, which may provide insights for law enforcement and researchers regarding where more attention is required since there may be some unmeasured factors causing higher crime trend in these areas.

Learning From Youth: Using Positive Outcomes to Evaluate Summer Youth Employment Programs

Summer Youth Employment Programs (SYEPs) help connect youth to opportunities for career exploration, skill development, and mentorship. Despite heightened investment in SYEPs, research regarding positive impacts is limited. Most of the common SYEP evaluation strategies are rooted in deficit thinking and focus on outcomes such as reducing violent crime, risk behaviors, gaps in unemployment, and increasing educational attainment. Despite recent shifts toward approaches that acknowledge structural oppression in adolescent research more broadly, evaluations of SYEPs often perpetuate a discourse of deficiency about marginalized communities by emphasizing disparities without acknowledging the systemic forces that create them. In this article, we utilize the Five Cs of Positive Youth Development to present an alternative set of outcomes identified from focus groups and surveys with youth ages 16 to 24 who participated in SummerWorks, a 10-week SYEP located in Washtenaw County, Michigan. Specifically, we find that SYEPs may help youth make the transition to adulthood, build community and increase their social capital, and access knowledge, resources, and opportunities. Through this approach, we hope to expand the literature on the impacts of SYEPs and encourage antiracist evaluation strategies that build on these findings and challenge deficit thinking.

Understanding the Multi-level Interactions Between Physical Environment and Neighborhood Characteristics in Assessing Vulnerability to Crime in Micro-places

Spatial crime risk assessment is based on the identification of the environmental conditions that could facilitate crime. Previous applications of this approach mainly rely on single-level analyses neglecting that different contextual factors are likely to influence crime at different geographical levels and to interact with one another in defining crime risk. This study proposes to innovate this approach by using a multi-level analysis and estimating the interaction terms among environmental features and neighborhood characteristics. An empirical test is conducted in a large urban area. The results prove that this method significantly increases the predictive capacity and favors more complete interpretations of the underlying criminogenic mechanisms, thus orienting more effective consequential actions.

Crime Risk Stations: Examining Spatiotemporal Influence of Urban Features through Distance-Aware Risk Signal Functions

Static indicators may fail to capture spatiotemporal differences in the spatial influence of urban features on different crime types. In this study, with a base station analogy, we introduced crime risk stations that conceptualize the spatial influence of urban features as crime risk signals broadcasted throughout a coverage area. We operationalized these risk signals with two novel risk scores, risk strength and risk intensity, obtained from novel distance-aware risk signal functions. With a crime-specific spatiotemporal approach, through a spatiotemporal influence analysis we examined and compared these risk scores for different crime types across various spatiotemporal models. Using a correlation analysis, we examined their relationships with concentrated disadvantage. The results showed that bus stops had relatively lower risk intensity, but higher risk strength, while fast-food restaurants had a higher risk intensity, but a lower risk strength. The correlation analysis identified elevated risk intensity and strength around gas stations in disadvantaged areas during late-night hours and weekends. The results provided empirical evidence for a dynamic spatial influence that changes across space, time, and crime type. The proposed risk functions and risk scores could help in the creation of spatiotemporal crime hotspot maps across cities by accurately quantifying crime risk around urban features.

THE CHARACTERISTICS AND COUNTERMEASURES FOR BIOSECURITY CRIMES UNDER THE NEW SITUATION

Today, China is facing many risk factors and great challenges in biosecurity crimes. Covered by non-traditional security, In terms of crime risk sources, crime threat forms, crime consequences, crime status, and crime trends，biosecurity crimes are different from traditional security crimes. Under the new situation, countermeasures to address biosecurity crimes include coordination of traditional and non-traditional security; construction of a prevention and control system based on big data; intensified personnel training; technology research and development; improvement of laws and regulations; combined governance of departments; effective international cooperation, and so on.