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A growing literature emphasizes violence occurring in public places. Yet, police seldom report such violence separately from violent incidents occurring elsewhere. This paper aims to distinguish assaults that occur in public vs private, outdoors vs indoors and in homes vs the night-time economy.

The authors reorganize police data to classify 1,062 assault locations for Boulder, Colorado, USA, 2020–2021, providing basic descriptive statistics that are seldom calculated or published.

In this city, almost two-thirds of police-recorded assaults occur away from home, often within night-time economy zones. Almost half of police-recorded assaults occur outdoors.

Public assaults are probably under-reported and under-recorded in police data. The share of assaults occurring in public is likely to vary greatly among cities, along with reporting practices.

Public assaults can create special problems for police and social services. Poor management of public space can contribute to such violence. Alcohol policy and enforcement in public places is especially relevant to public assaults. Poor urban design might explain some of the problem.

Public assaults are seen by many people and may do extra harm to children and even adults.

Police reports and academic work based on them seldom distinguish public from private assaults and seldom enumerate outdoor assaults in comparison to those indoors. In addition, statistics estimating violence in the night-time economy might not compare risks to other settings.

Introduction The Department of Electrical Engineering (EE) and Computer Science (CS) educates future national defence leaders in the theory and practice of its two disciplines and supports the overall USMA purpose of “providing the nation with leaders of character who serve the common defense”. Electromagnetic field theory and applications are fundamental to electrical engineering and play an important role in the Department's curriculum. In 1986, the Department began a modernization programme to upgrade its engineering curriculum, facilities, and equipment. This article describes the electromagnetics instructional thread in the curriculum and the laboratory facilities supporting that instruction.

This chapter presents empirical evidence on the effects of attributional retraining (AR), a motivation-enhancing treatment that can offset maladaptive explanatory mind-sets arising from adverse learning experiences. The evidence shows that AR is effective for assisting college students to adapt to competitive and challenging achievement settings.

This chapter describes the characteristics of AR protocols and details three primary advances in studying AR efficacy in terms of achievement performance, psychosocial outcomes, and processes that mediate AR-performance linkages. The psychological mechanisms that underpin AR effects on motivation and performance are outlined from the perspective of Weiner’s (1974, 1986, 2012) attribution theory.

Laboratory and field studies show that AR treatments are potent interventions that have short-term and long-lasting psychosocial, motivation, and performance benefits in achievement settings. Students who participate in AR programs are better off than their no-AR counterparts not just in their cognitive and affective prospects, but they also outperform their no-AR peers in class tests, course grades, and grade-point-averages, and are more persistent in terms of course credits and graduation rates.

This paper contributes to the emerging literature on treatment interventions in achievement settings by documenting key advances in the development of AR protocols and by identifying the next steps critical to moving the literature forward. Further progress in understanding AR efficacy will rest on examining the analysis of complex attributional thinking, the mediation of AR treatment effects, and the boundary conditions that moderate AR treatment efficacy.

The cognitive sciences, having emerged in the second half of the twentieth century, are recently experiencing a spectacular renewal, which cannot leave unaffected any discipline that deals with human behavior. The primary motivation for our project has been to weigh up the impact that this ongoing revolution of the sciences of the mind is likely to have on social sciences – in particular, on economics. The idea was to gather together a diverse group of social scientists to think about the following questions. Have the various new approaches to cognition provoked a crisis in economic science?¹ Should we speak of a scientific revolution (in the sense of Kuhn) also in contemporary social sciences, occurring under the growing influence of the cognitive paradigm? Above all, can a more precise knowledge of the complex functioning of the human mind and brain advance in any way the understanding of economic decision-making?

The purpose of this paper is to better understand the role of closeness and the relationships between social media influencers and their followers, and, more specifically, how social media influencers can effectively manage their human brands.

Two studies were conducted to explore social media influencers. Qualitative content analysis and modeling with path analysis were used to analyze the data.

Results found attractiveness and likeability to positively predict attitudes toward the influencer, word-of-mouth and purchase intentions, whereas similarity only predicted word-of-mouth from the follower. Closeness served as a moderator but had different effects. Closeness positively moderated the effect of attractiveness on purchase intentions; however, it had a negative effect with similarity on purchase intentions. Moreover, closeness moderated the effect of likeability on attitude toward the influencer.

This study was limited by the student sample as well as the students’ self-identification of a social media influencer. Future research should include experimental design manipulating well-known/followed or fictional social media influencers on different social media.

This paper explores the characteristics of social media influencers as well as the potential outcomes associated with influencers on social media. The implications for marketers and advertisers include a better understanding of how consumers engage with influencers on social media.

The role of closeness is identified as a moderator of consumers’ behaviors toward social media influencers.

Novel micro‐insurance schemes are emerging to help the poor better deal with droughts and other disasters. Climate change is projected to increase the intensity and frequency of disasters and is already adding stress to actual and potential clients of these schemes. As well, insurers and reinsurers are increasingly getting worried about increasing claim burdens and the robustness of their pricing given changing risks. The purpose of this paper is to review and suggest ways to methodologically tackle the challenges regarding the assessment of drought risk and the viability of index‐based insurance arrangements in the light of changing risks and climate change.

Based on novel modeling approaches, the authors take supply as well as demand side perspectives by combining risk analysis with regional climate projections and linking this to household livelihood modeling and insurance pricing. Two important examples in Malawi and India are discussed, where such schemes have been or are about to be implemented.

The authors find that indeed micro‐insurance instruments may help low‐income farming households better manage drought risk by smoothing livelihoods and reducing debt, thus avoiding poverty traps. Yet, also many obstacles to optimal design, viability and affordability of these schemes, are encountered. One of those is climate change and the authors find that changing drought risk under climate change would pose a threat to the viability of micro‐insurance, as well as the livelihoods of people requesting such contracts.

The findings and suggestions may corroborate the case for donor support for existing or emerging insurance arrangements helping the poor better cope with climate variability and change. Furthermore, a closer linkage between climate and global change models with insurance and risk management models should be established in the future, which could be beneficial for both sides.

Economics laboratories have become the primary locations of experimental economics research by the 1990s. They were a result of a decade long development from ad hoc opportune places to dedicated, purpose designed spaces. The distinctive feature of the economics laboratory and its key instrument became networked computers running custom-built software. However, the history of the economics laboratory is not just a history of evolving technology. I argue in this article that it is mainly a history of learning how to build an experimental economics community. Only a functioning community was able to change a physical place to a laboratory space. The distinction between place and space originates in the work of Michael de Certeau and I use it to analyze the evolution of economics laboratories. To this end, I analyze the case of Austin Hoggatt’s Management Science Laboratory at Berkeley in the 1960s as it illustrates the indispensability of creating a community centered on the laboratory. In contrast, the laboratories in Arizona and at Caltech since the 1980s, and in Amsterdam since the 1990s have become successful spaces, because, unlike Hoggatt, they focused equally on community building as on infrastructure and technology. This gave rise to social infrastructure and division of labor in the laboratory space.

In this chapter, we evaluate the employment effects of job-creation schemes (JCS) on the participating individuals in Germany. JCS are a major element of active labour market policy in Germany and are targeted at long-term unemployed and other hard-to-place individuals. Access to very informative administrative data of the Federal Employment Agency justifies the application of a matching estimator and allows us to account for individual (group-specific) and regional effect heterogeneity. We extend previous studies for Germany in four directions. First, we are able to evaluate the effects on regular (unsubsidised) employment. Second, we observe the outcomes of participants and non-participants for nearly three years after the programme starts and can therefore analyse medium-term effects. Third, we test the sensitivity of the results with respect to various decisions that have to be made during implementation of the matching estimator. Finally, we check if a possible occurrence of a specific form of ‘unobserved heterogeneity’ distorts our interpretation. The overall results are rather discouraging, since the employment effects are negative or insignificant for most of the analysed groups. One exception are long-term unemployed individuals who benefit from participation at the end of our observation period. Hence, one policy implication is to address the programmes to this problem group more closely.