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.     

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.     

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.     

The Modeling and Seasonal Adjustment of Weekly Observations

Several important economic time series are recorded on a particular day every week. Seasonal adjustment of such series is difficult because the number of weeks varies between 52 and 53 and the position of the recording day changes from year to year. In addition certain festivals, most notably Easter, take place at different times according to the year. This article presents a solution to problems of this kind by setting up a structural time series model that allows the seasonal pattern to evolve over time and enables trend extraction and seasonal adjustment to be carried out by means of state-space filtering and smoothing algorithms. The method is illustrated with a Bank of England series on the money supply.     

A Bootstrap Stationarity Test for Predictive Regression Invalidity

In order for predictive regression tests to deliver asymptotically valid inference, account has to be taken of the degree of persistence of the predictors under test. There is also a maintained assumption that any predictability in the variable of interest is purely attributable to the predictors under test. Violation of this assumption by the omission of relevant persistent predictors renders the predictive regression invalid, and potentially also spurious, as both the finite sample and asymptotic size of the predictability tests can be significantly inflated. In response, we propose a predictive regression invalidity test based on a stationarity testing approach. To allow for an unknown degree of persistence in the putative predictors, and for heteroscedasticity in the data, we implement our proposed test using a fixed regressor wild bootstrap procedure. We demonstrate the asymptotic validity of the proposed bootstrap test by proving that the limit distribution of the bootstrap statistic, conditional on the data, is the same as the limit null distribution of the statistic computed on the original data, conditional on the predictor. This corrects a long-standing error in the bootstrap literature whereby it is incorrectly argued that for strongly persistent regressors and test statistics akin to ours the validity of the fixed regressor bootstrap obtains through equivalence to an unconditional limit distribution. Our bootstrap results are therefore of interest in their own right and are likely to have applications beyond the present context. An illustration is given by reexamining the results relating to U.S. stock returns data in Campbell and Yogo (2006 Campbell, J. Y. and Yogo, M. (2006), “Efficient Tests of Stock Return Predictability,” Journal of Financial Economics, 81, 27–60.[Crossref], [Web of Science ®] , [Google Scholar]). Supplementary materials for this article are available online.     

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.     

Impact of an Overt Response System on Staff Performance and Maintenance of Computer-Based Instruction

Interactive Computer Based Instruction (CBI) systems involve teaching strategies to facilitate greater response opportunities during training in an effort to improve learner performance. The current study investigated the effect of online staff training videos with and without overt response requirements on posttest and maintenance test scores across six block-randomized instructional modules for four employees of a university located in the southeastern region of the United States. The overt response consisted of multiple-choice questions administered throughout select teaching modules using an alternating treatment design. Findings suggest that learning occurred as a result of the CBI training; however, the effectiveness of the overt response system varied across individuals, with no discernible differentiation between learning gains associated with response requirements. Other areas of research for expanding the efficacy of CBI and overt response systems are highlighted.     

Self-management of a chronic illness: An exploratory study on the role of spirituality among older African American women

Living with a chronic illness is an experience characterized by changes in self-management behavior. Few studies have addressed the role of spirituality in the self-management of a chronic illness among older African American women. The purpose of this exploratory study was to understand the role of spirituality in the self-management of chronic illness. Data from a sample of 10 African American women were collected from semi-structured interviews and analyzed for common themes through narrative analysis. Four themes emerge from the linkage of spirituality and self-management. Understanding this experience will assist public health providers in creating culturally appropriate health education interventions.