Feminist and empowerment theory and social work practice

Feminist and empowerment theories are especially important to the understanding of individual and sociopolitical levels of social work assessment and intervention. Incorporating feminist and empowerment approaches in practice will provide social workers with the knowledge, values and skills most likely to promote human rights and social justice. In this paper, we present an overview of both theories and illustrate them with a case example.     

When Working Hard Is Not Enough for Female and Racial/Ethnic Minority Apprentices in the Highway Trades

Drawing on employment records, qualitative interviews, and a survey, we explore the experiences of apprentices in the highway trades in Oregon. We demonstrate that female and racial/ethnic minority apprentices have lower rates of recruitment and retention and disproportionately face challenges with interpersonal interactions, hiring practices, and supervisory practices. Yet, we find a pervasive narrative that attributes apprentices' success to “hard work,” which contributes to the legitimacy of these inequalities. Consistent with the conceptualization of work organizations as inequality regimes, we argue that the apprenticeship system has policies, practices, and ideologies that are on the surface gender and race/ethnicity neutral, yet lead to the perpetuation of inequalities.     

Tasmania Together? A disability critique of a social plan

The 'Tasmania Together' social futures plan for Tasmania is critically examined. Authored by a Tasmanian Government appointed Community Leaders Group, on behalf of the people of Tasmania, the plan is supposed to deliver a better Tasmanian society by 2020, based upon community consultation. Rather than a step-forward in democracy, the process serves to remove the democratic rights of people, especially those who are disadvantaged. A critique from a disability perspective is offered, which suggests that this social plan constitutes a form of institutionalised disablism.     

Bayesian inference for a discretely observed stochastic kinetic model

The ability to infer parameters of gene regulatory networks is emerging as a key problem in systems biology. The biochemical data are intrinsically stochastic and tend to be observed by means of discrete-time sampling systems, which are often limited in their completeness. In this paper we explore how to make Bayesian inference for the kinetic rate constants of regulatory networks, using the stochastic kinetic Lotka-Volterra system as a model. This simple model describes behaviour typical of many biochemical networks which exhibit auto-regulatory behaviour. Various MCMC algorithms are described and their performance evaluated in several data-poor scenarios. An algorithm based on an approximating process is shown to be particularly efficient.     

The Role of Shocks in Employee Turnover*

This paper reports the findings from a recent study of nurse leavers at eight large hospitals in the National Health Service (NHS) of England and Wales. The study develops and extends an influential theory of employee turnover by describing how for some leavers a single, jarring event or shock triggers the decision to quit. By elaborating on the nature of shocks for this sample of 352 nurse leavers, the paper allows for improved understanding of nursing turnover and thus offers an example of relevant management research. The analysis of shock illustrates how conventional research methodologies can lead to a distorted picture of turnover. This has wider implications, both for any organization wishing to manage turnover effectively and for future research. The paper adds to the limited body of empirical analysis on actual leavers, thereby contributing to an ongoing methodological debate concerning the use of proxy variables. By highlighting flaws in the dominant methodology used to study turnover, the paper offers an example of management research that is also rigorous, and thus ‘pragmatic’.     

Coming Full Circle: Reoccurring Career Development Trends in Schools

Current state and national mandates focusing on academic achievement have drawn critical counseling resources away from career development. As the world of work radically changes and economic situations remain uncertain, the call for a return to school counseling roots based in career guidance has never been louder. The authors explore reoccurring career guidance trends throughout the history of school counseling to expand awareness of the basis of today's career and technical education discussions and increase understanding of the interconnectedness of career guidance and counseling and educational reform.     

In search of rigor, relevance, and legitimacy: what drives the impact of publications?

In this study, we introduce the concept of legitimacy to the rigor-relevance debate and investigate empirically how rigor, relevance, and legitimacy are related to the process of knowledge dissemination within a research field. We argue that this analysis has been a missing piece in the debate on rigor and relevance when institutional logics about what constitutes both elements lead researchers to act according to what they perceive to be appropriate behavior in the research field. We draw on insights from the micro and macro levels of institutional theory to show how researchers aiming to bestow legitimacy on their own work conform to these “rules of the game”. Using meta-analytical techniques, we focus on the field of strategic entrepreneurship and analyze how rigor- and relevance-related characteristics of studies in this field are linked to their legitimacy and therefore to the impact they have in the research community.     

Bayes linear analysis for graphical models: The geometric approach to local computation and interpretive graphics

This paper concerns the geometric treatment of graphical models using Bayes linear methods. We introduce Bayes linear separation as a second order generalised conditional independence relation, and Bayes linear graphical models are constructed using this property. A system of interpretive and diagnostic shadings are given, which summarise the analysis over the associated moral graph. Principles of local computation are outlined for the graphical models, and an algorithm for implementing such computation over the junction tree is described. The approach is illustrated with two examples. The first concerns sales forecasting using a multivariate dynamic linear model. The second concerns inference for the error variance matrices of the model for sales, and illustrates the generality of our geometric approach by treating the matrices directly as random objects. The examples are implemented using a freely available set of object-oriented programming tools for Bayes linear local computation and graphical diagnostic display.