Culturally meaningful networks: on the transition from military to civilian life in the United Kingdom

This article introduces the Culturally Meaningful Networks (CMN) approach. Following a pragmatist perspective of social mechanisms more broadly, it develops and demonstrates an approach to understanding networks that incorporates both structure and meaning and that leverages time to understand how these aspects influence each other. I apply this approach to investigate a longstanding puzzle about why some of those who leave military service for civilian life fare well, and others badly. In a mixed-methods analysis, I follow a sample of individuals moving through the transition from military to civilian life in the contemporary United Kingdom. I find that the higher the proportion of alters (i.e., “contacts”) with a military background in the networks of leavers before discharge, the worse they fare after discharge. The CMN approach helps me locate a specific structural embedding that explains the presence or absence of durable cultural frames that set the context for the actual experience of the transition and cause problems during it. Attention to the temporal unfolding of network structure and social meaning is essential to bringing out this finding. By re-embedding networks within people’s experiences over time, the CMN approach helps grasp the distinctions by which leavers understand their interactions. I conclude by arguing that the CMN approach has implications for network sociology and cultural sociology that go beyond this substantive case.     

A Unified Approach to Structural Change Tests Based on ML Scores,F Statistics,and OLS Residuals

This paper presents an easy-to-compute semi-parametric (SP) method to estimate a simple disequilibrium model proposed by Fair and Jaffee (1972). The proposed approach is based on a non-parametric interpretation of the EM (Expectation and Maximization) principle (Dempster et al; 1977) and the least squares method. The simple disequilibrium model includes the demand equation, the supply equation, and the condition that only the minimum of quantity demanded and quantity supplied is observed. The method used here allows one to consistently estimate the disequilibrium model without fully specifying the distribution of error terms in both demand and supply equations. Our Monte Carlo study suggests that the proposedestimator is better than the normal maximum likelihood estimator under asymmetric error distributions. and comparable to the nlaximunl likelihood estimator under synirnetric error distributions in finite samples. Aggregate U.S. labor market data from Quandt and Rosen (1988) is used to illustrate the procedure.     

Policy integration: mapping the different concepts

A growing number of studies have examined the collaboration of actors from two or more policy domains in order to integrate aims and concerns derived from one policy domain into another. In our literature review, we refer to this empirical phenomenon as ‘policy integration’, exemplified by the Health in All Policies approach. Despite the wealth of literature on the subject, the scientific community only has access to a portion of the insights that have come out of this field of research, due primarily to the fact that policy integration is discussed using a variety of different terms, which tend to be specific to the policy domain under investigation. To facilitate a more inclusive scientific debate on policy integration, we provide a comprehensive overview of the different terminologies associated with policy integration and analyse the recurring themes in the respective literature strands. What is the motivation for policy-makers to promote policy integration? What is the design of the instruments used for policy integration? How does policy integration affect the policy-making process? And how well does policy integration perform? These are the four questions guiding our study.     

Cortisol on Sunday as indicator of recovery from work: Prediction by observer ratings of job demands and control

Several considerations guided the research reported in this paper. First, recovery is pivotal for preventing stressful experiences from inducing long-term consequences. Second, cortisol levels under relaxed conditions constitute a good baseline measure. Third, there are many calls to avoid common method problems. Therefore, the Job Demands–Control (JDS) model, one of the most prominent models in occupational stress, should be tested by a combination of observation, self-report, and physiological data in terms of predicting recovery-related variables. In a sample of 53 Swiss employees, we assessed the JDS variables, demands and control, by systematic observation, fatigue at the end of work as an indicator of short-term recovery by questionnaire, and delayed recovery by baseline levels of cortisol on a Sunday under relaxing conditions. In line with expectations, regression analyses showed an impact of job demands and control on Sunday cortisol levels, and this effect was fully mediated by after work fatigue. Contrary to expectations, there was no significant interaction between job demands and control. Demonstrating that job demands and control predict after-work fatigue as well as a delayed physiological marker of recovery, these findings suggest that high after-work fatigue may entail costs to the individual’s physiological systems.     

Estimation of the characteristics of a Lévy process

We consider a Lévy process that is e.g. used in finance to model stock price developments. We want to estimate the characteristics of that process, based on historical data where we assume that we have discrete, high frequency observations. We introduce a threshold estimation method and show consistency and in the case of finite activity asymptotic normality of these estimators.