An Approach to Assessing the Impacts of Incident-Free Transportation of Radioactive Materials: II. Highway Transportation

Annual radiation doses and risks to the public living near, and traveling on, public highways, and occupational doses are calculated for highway shipments of radioactive materials under accident-free and incident-free conditions (i.e., under normal transportation conditions). The database developed by Sandia National Laboratories is used, and calculations are made using RADTRAN 4.0. This report is one of two reports estimating radiological risk associated with transportation of radioactive materials.     

Bayesian variable selection and regularization for time–frequency surface estimation

Summary.  We describe novel Bayesian models for time–frequency inverse modelling of non-stationary signals. These models are based on the idea of a Gabor regression , in which a time series is represented as a superposition of translated, modulated versions of a window function exhibiting good time–frequency concentration. As a necessary consequence, the resultant set of potential predictors is in general overcomplete—constituting a frame rather than a basis—and hence the resultant models require careful regularization through appropriate choices of variable selection schemes and prior distributions. We introduce prior specifications that are tailored to representative time series, and we develop effective Markov chain Monte Carlo methods for inference. To highlight the potential applications of such methods, we provide examples using two of the most distinctive time–frequency surfaces—speech and music signals—as well as standard test functions from the wavelet regression literature.     

On the Utility of Robust and Resampling Procedures1

Abstract Kassab (1990) makes an important methodological contribution by urging the use of robust regression methods in the study of community economic impacts and by indicating the utility of the bootstrap in assessing standard errors in robust regression. By introducing the notion of a contaminating distribution, we reconcile differences between her claim that ordinary least squares (OLS) regression is biased when outliers are present and standard linear model theory that does not make assumptions about the shape of the residual distribution in proving OLS an unbiased estimator. The contaminating distribution provides a framework for rural sociologists to link their statistical assumptions to a substantive understanding of the phenomena being studied. We suggest an alternative regression estimation strategy that may be more robust than the technique she uses. We also discuss an approach to bootstrapping that is more appropriate for macro-level social indicator data than the one she describes. An appendix discusses the software available for implementing these methods.     

Beyond normalization and impairment: theorizing subjectivity in learning difficulties – theory and practice

Normalization and social role valorization continue to play a central role in shaping debates and practice relating to learning difficulties. In the context of recent arguments this paper draws on the work of Foucault to deconstruct these theories. Foucault’s work alerts us to a conceptual confusion at their heart which reproduces a common but problematic individual–society dualism. There is an implicit, and problematic, presence in the theories of a pre‐social individual conceived as having essential impairments and who is passive in the face of negative socialization. We propose that Foucault’s ‘ethical’ domain of inquiry, with its concern for how people actively understand themselves and govern their conduct in relation to specific values and a ‘truth’ that they are obliged to recognize in themselves, provides the basis for returning the individual‐as‐subject to theories in an active, critical manner.     

Evaluating the Efficacy of a Mental Models Approach for Improving Occupational Chemical Risk Protection

Chemical risk protection in the workplace relies partly on informing workers about possible risks using material safety data sheets (MSDS). This article reports on phase 2 of a project (phase 1 reported in Cox et al.), which employed a mental models approach to improve on data sheets as communicative interventions for perchloroethylene in dry cleaning and rosin-based solder flux in the electronics industry within small businesses in the United Kingdom (small enterprises (SEs) < 25 employees in the workplace). It focuses on the efficacy of a multimethod evaluation strategy to assess (1) the capacity of a mental models approach to yield contextually relevant data for intervention design and (2) the effectiveness of the strategy itself in validating the mental models data. The evaluation was conducted using postal questionnaires and semi-structured verbal protocols to provide responses to the alternative intervention content and to prioritize risk messages. User discussion groups were then employed, particularly as a means of establishing whether contextual information could be obtained that would differ qualitatively from the kind elicited through individual (semi) structured methods. We conclude that the mental models approach as part of an iterative process including systematic multimethod evaluation is successful in supporting the design of relevant communications to the users of chemicals. The overall viability of communicative interventions in the context of health and safety in small businesses remains in question. Future research might aim to develop a more holistic approach to interventions in complex occupational contexts.     

Should I Stay or Should I Go? Explaining Turnover Intentions with Organizational Identification and Job Satisfaction*

The social identity approach is a powerful theoretical framework for the understanding of individuals' behaviour. The main argument is that individuals think and act on behalf of the group they belong to because this group membership adds to their social identity, which partly determines one's self‐esteem. In the organizational world, social identity and self‐categorization theories state that a strong organizational identification is associated with low turnover intentions. Because identification is the more general perception of shared fate between employee and organization, we propose that the relationship between identification and turnover will be mediated by job satisfaction as the more specific evaluation of one's task and working conditions. In four samples we found organizational identification feeding into job satisfaction, which in turn predicts turnover intentions.