The Social Construction of Asperger Syndrome: The pathologising of difference?

This article poses the question 'Is Asperger Syndrome (AS) a disorder or a neurological difference that has been socially constructed as a disorder?' AS is currently defined within the medical paradigm as a developmental disorder. Alternative conceptualisations of Asperger Syndrome have largely been absent within the academic discourse on AS. Drawing on the emerging field of disability studies we examine how the diagnostic category of AS has been socially constructed. Our contention is that Asperger Syndrome has been readily adopted as a category because of its value as a category of special education. In other words, the school is a pivotal institution in the dissemination of AS as a category. Within the framework of special needs AS is viewed as a social disability and the aim of professional interventions is to help to rehabilitate or 'normalise' the child. In attempting to re-frame this conceptualisation of AS it is important to shift the emphasis from issues of diagnosis and evaluation to examining the social implications of representing children as having AS.     

Review Essay: Constructing the Sociology of Social Problems: Spector and Kitsuse Twenty-Five Years Later

Sociological Forum -     

A solution of the externality problem using strategic matching

This paper develops a Coase-like solution of the problem of inducing Pareto optimal behavior in the presence of reciprocal externalities. In place of Coasean direct compensation between the parties to an externality problem, actors strategically match each other's externality-producing activity, and thus induce counterparts to internalize the external benefits or costs of their actions. The analysis suggests a general framework for analyzing social interactions in the presence of reciprocal externalities. As an application of the theory, a solution of the duopoly problem is noted.We are indebted to L. Danziger, D. Samet, participants in faculty seminars at Bar-Ilan and New York Universities and at the University of Maryland, and two anonymous referees for helpful comments and discussions. All remaining errors are our own.     

Nonparametric smoothing in the analysis of air pollution and respiratory illness

While most of epidemiology is observational, rather than experimental, the culture of epidemiology is still derived from agricultural experiments, rather than other observational fields, such as astronomy or economics. The mismatch is made greater as focus has turned to continue risk factors, multifactorial outcomes, and outcomes with large variation unexplainable by available risk factors. The analysis of such data is often viewed as hypothesis testing with statistical control replacing randomization. However, such approaches often test restricted forms of the hypothesis being investigated, such as the hypothesis of a linear association, when there is no prior empirical or theoretical reason to believe that if an association exists, it is linear. In combination with the large nonstochastic sources of error in such observational studies, this suggests the more flexible alternative of exploring the association. Conclusions on the possible causal nature of any discovered association will rest on the coherence and consistency of multiple studies. Nonparametric smoothing in general, and generalized additive models in particular, represent an attractive approach to such problems. This is illustrated using data examining the relationship between particulate air pollution and daily mortality in Birmingham, Alabama; between particulate air pollution, ozone, and SO₂ and daily hospital admissions for respiratory illness in Philadelphia; and between ozone and particulate air pollution and coughing episodes in children in six eastern U.S. cities. The results indicate that airborne particles and ozone are associated with adverse health outcomes at very low concentrations, and that there are likely no thresholds for these relationships.     

Achieving the indeterminate: Accomplishing degrees of certainty in life and death situations

This paper explores technology's pivotal position at the intersection of control and uncertainty. It examines two areas: Intensive Care and a Labour Ward. Building on the work of Davis (1960), it argues that certainty and uncertainty are socially constructable and reconstructable. This is actively achieved by the deployment of strategies involving particular paradigms (the biomedical model) and artefacts (medical technology). Power lies in control over knowledge and the structures and practices which sustain it, including those embedded in advanced technology. The contribution of medical technology to the achievement of certainty in Intensive Care and end-game Obstetrics (the Labour Ward) is considered. Achieved certainty in medical situations is seen as: the structured masking of uncertainty by the application of medical iconography, artefacts and techniques to create the illusion of certainty. The accomplishment of uncertainty in Obstetrics (as a precursor to technological intervention) is also explored. The accomplishment of uncertainty in medical situations is seen as associated with the structured projection of uncertainty, involving using medical discourse rooted in the medical paradigm to exaggerate the generality of risk and the probability of pathology. It is argued that the highly structured and routinised settings of ICU and the labour Ward, not only aid control by the medical profession but diminish perceptions of uncertainty.     

Why Did House Members Vote for H.R. 4437?1

This article examines why members of the U.S. House of Representatives voted for H.R. 4437, the controversial 2005 bill to construct a 700‐mile immigration barrier along the U.S.‐Mexican border and to criminalize illegal presence and aid to undocumented immigrants. Logit analysis suggests that being a first‐term House member or a Republican and representing a district that was in the South or the West or heavily blue‐collar substantially boosted the odds of supporting H.R. 4437. If a member's district was disproportionately Asian, Latino, or, especially, African American, he or she was instead more likely to oppose the measure.     

The limitations of using school league tables to inform school choice

Summary. In England, so-called 'league tables' based on examination results and test scores are published annually, ostensibly to inform parental choice of secondary schools. A crucial limitation of these tables is that the most recent published information is based on the current performance of a cohort of pupils who entered secondary schools several years earlier, whereas for choosing a school it is the future performance of the current cohort that is of interest. We show that there is substantial uncertainty in predicting such future performance and that incorporating this uncertainty leads to a situation where only a handful of schools' future performances can be separated from both the overall mean and from one another with an acceptable degree of precision. This suggests that school league tables, including value-added tables, have very little to offer as guides to school choice.     

Time Series Models for Count or Qualitative Observations

Time series sometimes consist of count data in which the number of events occurring in a given time interval is recorded. Such data are necessarily nonnegative integers, and an assumption of a Poisson or negative binomial distribution is often appropriate. This article sets ups a model in which the level of the process generating the observations changes over time. A recursion analogous to the Kalman filter is used to construct the likelihood function and to make predictions of future observations. Qualitative variables, based on a binomial or multinomial distribution, may be handled in a similar way. The model for count data may be extended to include explanatory variables. This enables nonstochastic slope and seasonal components to be included in the model, as well as permitting intervention analysis. The techniques are illustrated with a number of applications, and an attempt is made to develop a model-selection strategy along the lines of that used for Gaussian structural time series models. The applications include an analysis of the results of international football matches played between England and Scotland and an assessment of the effect of the British seat-belt law on the drivers of light-goods vehicles.