Search results

This chapter focuses on the objectives of historical interpretation (particularly teaching objectives outside of the traditional name- and date-driven curriculum), ideas that lead to creating a safe environment for students to be willing to try character portrayal themselves, content typically taught using this strategy, and successfully implemented sample lessons and activities by the authors that effectively utilize and harness the power of historical interpretation. These activities involve intense and intentional skill–based instruction that scaffolds students throughout their coursework, filling the school year with meaningful student-researched and student-produced historical interpretation. The authors discuss their teaching philosophy in relation to history and social studies, explaining why historical interpretation benefits teaching and learning. Through teacher- and student-driven character portrayals, the authors have created vibrant, secure classroom environments where students become responsible for their own learning and enthusiastic about research, writing, and performing. The chapter contains recommendations for coaching students in artifact analysis, performance, historical thinking strategies, storytelling, and creative writing. While they acknowledge that living history is not a “one-size-fits-all” solution to teaching history and social studies, they demonstrate that the unique learning culture that can result, providing student reflections to illustrate that point. The authors include and explain several effective resources that they have developed for student analysis of artifacts/objects, for guiding historical thinking, and for researching and writing. The chapter concludes with suggestions for individual and large group performance activities and advice on how to grade living history projects, keeping learning in mind as a component of holistic grading of creative student products.

Massively parallel desktop computing capabilities now well within the reach of individual academics modify the environment for posterior simulation in fundamental and potentially quite advantageous ways. But to fully exploit these benefits algorithms that conform to parallel computing environments are needed. This paper presents a sequential posterior simulator designed to operate efficiently in this context. The simulator makes fewer analytical and programming demands on investigators, and is faster, more reliable, and more complete than conventional posterior simulators. The paper extends existing sequential Monte Carlo methods and theory to provide a thorough and practical foundation for sequential posterior simulation that is well suited to massively parallel computing environments. It provides detailed recommendations on implementation, yielding an algorithm that requires only code for simulation from the prior and evaluation of prior and data densities and works well in a variety of applications representative of serious empirical work in economics and finance. The algorithm facilitates Bayesian model comparison by producing marginal likelihood approximations of unprecedented accuracy as an incidental by-product, is robust to pathological posterior distributions, and provides estimates of numerical standard error and relative numerical efficiency intrinsically. The paper concludes with an application that illustrates the potential of these simulators for applied Bayesian inference.

The number of reported cases for Japanese Penal Code offenses amounted to 2.5 million in 1997 and increased every year, reaching 3.6 million in 2002 and 2003. However, the number decreased from 2004 to 2008 to 2.5 million. Almost throughout the same period, the number of cases and persons cleared remained comparatively steady between 1.3 and 1.5 million and 1 and 1.2 million respectively, but the latter finally fell below one million in 2011. In this chapter I describe such a rise and fall as a “Mt. Fuji-line” that appears as a mountain-shaped curve on a graph.

The Japanese government reacted to the increase of crimes, which was seen as a reflection of a weakened or broken security and safety. The most effective policy, it was thought therefore, was to increase the number of policemen. This policy followed the strategy of New York City, made famous by its then Mayor Giuliani, who declared “A War on Crimes” and increased the number of police officers by ten thousand to revive New York from “A Crime City.” As criminologists have experienced so-called “labeling shocks” and learned from the approach of symbolic interactionism, criminologists can no longer simply accept that statistical data reflect weakened or broken security issues. Agencies of criminal justice, especially police officers, use such data as statistical evidence to show that the crime situation got worse.

I argue that the rise and fall of crimes, especially the increasing and decreasing number of reported cases, reflects changes of crime control policies. I analyze the Mt. Fuji-line from 1998 to 2011. The increase of crimes as well as the weakened or broken security and safety functioned as evidence that justified the reinforcement of police power and a new criminal justice shift for a lay judge system in the rising phase (1998–2003). Since the concept of a bigger justice system needs, however, lots of personnel and material sources, the Japanese government eventually gave up sustaining it. Agencies used their discretion to skip petty crimes and divert suspects because of a reduction of excessive burdens and inappropriate prison population, but they stepped into a new stage to adjust their burdens, keeping their own empowered framework of criminal justice system. These changing policies resulted in the reduction of crime in a falling phase (2004–2011).

These phenomena are explained from the viewpoint of Jürgen Habermas’ crisis theory. I conclude that the framework and capacity of the Japanese criminal justice system grew far bigger and that original functions of crime control through criminal procedure became weaker by being outsourced to other peripheral social systems and agencies. Thus the crime control system has been successful in bringing about a net-widening effect.

Advances in Econometrics is a series of research volumes first published in 1982 by JAI Press. The authors present an update to the history of the Advances in Econometrics series. The initial history, published in 2012 for the 30th Anniversary Volume, describes key events in the history of the series and provides information about key authors and contributors to Advances in Econometrics. The authors update the original history and discuss significant changes that have occurred since 2012. These changes include the addition of five new Senior Co-Editors, seven new AIE Fellows, an expansion of the AIE conferences throughout the United States and abroad, and the increase in the number of citations for the series from 7,473 in 2012 to over 25,000 by 2022.

The deadhead subculture – centered around the band Grateful Dead – has been active for 50+ years. Despite its longevity, academic work is sparse compared to other music subcultures. Given its durability and resilience, this subculture offers an opportunity to explore subcultural development and maintenance. I employ a contemporary, symbolic interactionist approach to trace the development of deadhead subculture and subcultural identity. Although identity is a basic concept in subculture research, it is not well defined: I suggest that the co-creation and maintenance of subcultural identity can be seen as a dialectic between collective identity and symbolic interactionist conceptions of individual role-identity.

The chapter considers the change of position of the Home Office on the value of randomised controlled trials (RCTs) in England and Wales which took place around 2003 after the end of the Crime Reduction Programme (CRP). Before the CRP Home Office researchers had shown little interest in RCTs; after it, they came close to arguing that no other kinds of evaluation research were worth doing. This represented a reversal of a position that had dominated Home Office thinking on the issue for almost 30 years – that RCTs were in general impractical and unlikely to produce clear-cut results. This view was based in part on the experience of RCTs in the 1970s, which led influential researchers to conclude that the method could not be transferred from medicine to criminal justice. But, disappointed with the lack of definite results from the CRP, the Home Office turned back to RCTs as a potential source of certainty about what works. The chapter considers two recent scholarly exchanges on the question, in relation to an evaluation of a community crime reduction programme, for which an experimental design was attempted but not achieved, and to Lawrence Sherman's recent advocacy of RCTs and his use of research on restorative justice as an example of the successful use of the method. The chapter argues that the restorative justice research, while of very high quality, does not provide as clear an example of the use of an RCT as Sherman claims, and concludes with some reflections on the inherent difficulties of criminal justice evaluation, and on the lack of a predictable, rational relationship between research quality and policy influence.

In recent years, it has become evident that self-regulation plays a central role in human functioning, including learning and achievement in school. Although there are different definitions of self-regulation, there is general consensus that it refers to a multi-component, iterative, self-steering process that targets one's own cognitions, feelings, and actions, as well as features of the environment for modulation in the service of one's own goals (Boekaerts, Maes, & Karoly, 2005). Educational psychologists agree that learning in the classroom involves cognitive and affective processing and is heavily influenced by social processes. This implies that students should be able and willing to regulate their cognitions, motivation, and emotions, as well as to adapt to the social context in order to facilitate their learning. Yet, there is at present neither a uniformly accepted definition of self-regulation nor that of self-regulated learning. Most theorists agree that self-regulation in the classroom is neither an all-or-none process nor a property of the learning system. Rather, it consists of multiple processes and components that interact in complex ways. Definitions have focused either on the structure of self-regulation, describing the different components of the self-regulation process, or on the processes that are involved.