Re‐framing the Analysis: A 3‐dimensional Perspective of Prisoners’ Children's Well‐being

This article highlights three dimensions to understanding children's well‐being during and after parental imprisonment which have not been fully explored in current research. A consideration of ‘time’ reveals the importance of children's past experiences and their anticipated futures. A focus on ‘space’ highlights the impact of new or altered environmental dynamics. A study of ‘agency’ illuminates how children cope within structural, material and social confines which intensify vulnerability and dependency. This integrated perspective reveals important differences in individual children's experiences and commonalities in broader systemic and social constraints on prisoners’ children. The paper analyses data from a prospective longitudinal study of 35 prisoners’ children during and after their (step) father's imprisonment to illustrate the arguments.     

Identity work in female‐led creative businesses

This study explores the identity work carried out by three female owner‐managers in creative industry businesses, identified in Government reports as a discriminatory industrial sector for women in the UK. Through the development of narratives by the owners and other participants, observation of practice and review of online and offline materials, three cases emerged. These showed overlapping, different identities developed and performed through identity work. Each presented rational and logical persona as business leaders despite observation showing extensive use of intuition and gut feeling in both creative and entrepreneurial aspects of the business. Intuition and gut feeling were seen as inappropriate at work as they belonged to the home sphere, emotionally based and therefore automatically unreliable. While occupying male stereotypes and avoiding the female realm of emotion at work, these women expressed femininity through their emphasis on the maternal, ‘being a good mother' as a desired ideal being embedded in work as well as home practice.     

Lives in limbo: Temporary Protected Status and immigrant identities

The United States formulates much of its immigration and refugee policy to match economic and political circumstances. We interpret these policy shifts as a set of graduated positions on immigration and refugee flows that attempts to discipline the lives of newcomers and, in so doing, shapes immigrant identities. In this article, we analyse the interplay between the US government and Salvadoran asylum applicants negotiating procedures that grant only temporary relief from deportation via the policy of Temporary Protected Status (TPS). We find that each policy shift results in the strategic renegotiation of asylum applicants’ identities so as to achieve the best opportunity for a successful outcome. Based on Foucault’s ideas of governmentality and Ong’s concept of flexible citizenship, we argue that what appears more superficially as a patchwork strategy of immigration laws and asylum practices may be theorized more deeply as a set of flexible responses by the state that turn on identity construction at different scales, and that aim to mediate transnational relations.     

LOG-PERIODOGRAM ESTIMATION OF LONG MEMORY VOLATILITY DEPENDENCIES WITH CONDITIONALLY HEAVY TAILED RETURNS

Many recent papers have used semiparametric methods, especially the log-periodogram regression, to detect and estimate long memory in the volatility of asset returns. In these papers, the volatility is proxied by measures such as squared, log-squared, and absolute returns. While the evidence for the existence of long memory is strong using any of these measures, the actual long memory parameter estimates can be sensitive to which measure is used. In Monte-Carlo simulations, I find that if the data is conditionally leptokurtic, the log-periodogram regression estimator using squared returns has a large downward bias, which is avoided by using other volatility measures. In United States stock return data, I find that squared returns give much lower estimates of the long memory parameter than the alternative volatility measures, which is consistent with the simulation results. I conclude that researchers should avoid using the squared returns in the semiparametric estimation of long memory volatility dependencies.     

CALGARY FAMILY INTERVENTION MODEL: ONE WAY TO THINK ABOUT CHANGE

This article defines and describes the Calgary Family Intervention Model (CFIM). CFIM is an organizing framework conceptualizing the intersect between a particular domain (i.e., cognitive, affective, or behavioral) of family functioning and a specific intervention offered by a health professional. Examples and discussion of interventions such as storying the illness experience, encouraging respite, and asking interventive questions are presented. CFIM is one way that health professionals can conceptualize about change.     

Was there a “golden past” for the introductory sociology textbook? A citation analysis of leading journals

Much debate over the years has centered around whether there was ever a “golden past” for the introductory sociology textbook, when high quality books influenced the development of scholarship and thinking. Some empirical evidence is added to this debate through an analysis of the citations to introductory sociology textbooks in all the articles and research notes appearing in theAmerican Journal of Sociology, theAmerican Sociological Review, andSocial Forces from 1960 to 1969 and from 1984 to 1993. The data show that, although seldom cited in recent journals, introductory sociology textbooks were often cited in the earlier period. The article concludes with some thoughts about why introductory sociology textbooks have had a declining influence on scholarship.     

Natural and social order at Walt Disney World; the functions and contradictions of civilising nature

Elias’ theory of the civilising process is used to show how the Walt Disney World Theme Parks construct social control over visitors without calling into question the official presentation of these visitors as free, choice‐making, experience seeking individuals. Particular attention is drawn to the manipulation of images of nature as either ‘wild’ or ‘civilised’ to code, respectively, forbidden and legitimate places for visitors. In doing so, WDW is able to maintain civilised, non‐coercive, discourse with its ‘guests’ who are, thus presented to themselves as responsible and self‐regulating persons. Attention is drawn to the contradiction that this strategy creates between ‘authentic’ and ‘civilised’ spectacle particularly in the presentation of animals. It is noted how this creates an imperative to show only civilised animal behaviour but which, in turn, limits the means that the Disney Corporation can adopt in order to create a space that is free from the intrusion of uncivilised nature.     

ELICITING A DIRECTED ACYCLIC GRAPH FOR A MULTIVARIATE TIME SERIES OF VEHICLE COUNTS IN A TRAFFIC NETWORK

The problem of modelling multivariate time series of vehicle counts in traffic networks is considered. It is proposed to use a model called the linear multiregression dynamic model (LMDM). The LMDM is a multivariate Bayesian dynamic model which uses any conditional independence and causal structure across the time series to break down the complex multivariate model into simpler univariate dynamic linear models. The conditional independence and causal structure in the time series can be represented by a directed acyclic graph (DAG). The DAG not only gives a useful pictorial representation of the multivariate structure, but it is also used to build the LMDM. Therefore, eliciting a DAG which gives a realistic representation of the series is a crucial part of the modelling process. A DAG is elicited for the multivariate time series of hourly vehicle counts at the junction of three major roads in the UK. A flow diagram is introduced to give a pictorial representation of the possible vehicle routes through the network. It is shown how this flow diagram, together with a map of the network, can suggest a DAG for the time series suitable for use with an LMDM.     

Loss functions for estimation of extrema with an application to disease mapping

It is often of interest to find the maximum or near maxima among a set of vector‐valued parameters in a statistical model; in the case of disease mapping, for example, these correspond to relative‐risk “hotspots” where public‐health intervention may be needed. The general problem is one of estimating nonlinear functions of the ensemble of relative risks, but biased estimates result if posterior means are simply substituted into these nonlinear functions. The authors obtain better estimates of extrema from a new, weighted ranks squared error loss function. The derivation of these Bayes estimators assumes a hidden‐Markov random‐field model for relative risks, and their behaviour is illustrated with real and simulated data.