A small sample confidence interval for autoregressive parameters

This paper is concerned with interval estimation of an autoregressive parameter when the parameter space allows for magnitudes outside the unit interval. In this case, intervals based on the least-squares estimator tend to require a high level of numerical computation and can be unreliable for small sample sizes. Intervals based on the asymptotic distribution of instrumental variable estimators provide an alternative. If the instrument is taken to be the sign function, the interval is centered at the Cauchy estimator and a large sample interval can be created by estimating the standard error of this estimator. The interval proposed in this paper avoids estimating this standard error and results in a small sample improvement in coverage probability. In fact, small sample coverage is exact when the innovations come from a normal distribution.     

Re‐thinking Disability,Work and Welfare

There is a wealth of evidence that disabled people experience far higher levels of unemployment and underemployment than non‐disabled peers. Yet hitherto sociologists have paid scant attention to the structural causes of this issue. Drawing on a socio/political or social model of disability perspective this paper argues for a reconfiguration of the meaning of disability and work in order to address this problem. It is also suggested that such a strategy will make a significant contribution to the struggle for a fairer and equitable global society.     

The Contribution of Social Movement Theory to Understanding Terrorism

The study of terrorism and political violence has been characterized by a lack of generalizable theory and methodology. This essay proposes that social movement theory can contribute a necessary conceptual framework for understanding terrorism and thus reviews the relevant literature and discusses possible applications. Terrorism is a form of contentious politics, analyzable with the basic social movement approach of mobilizing resources, political opportunity structure, and framing. Cultural perspectives call attention to issues of collective identity that allow for sustained militancy, and movement research recommends alternative conceptions of terrorist networks. Previous research on movement radicalization, repression, and cycles of contention has direct bearing on militancy. Emerging perspectives on transnational collective action and the diffusion of tactics and issues informs an understanding of contemporary international terrorism. Research on movement outcomes suggests broader ways of considering the efficacy of political violence. Finally, methodological debates within the study of social movements are relevant for research on terrorism. In sum, a social movement approach to terrorism has much to contribute, and research on terrorism could have important extensions and implications for social movement theory.     

Sampling issues in the administration of justice

Colin Aitken first became interested in sampling in the context of the administration of justice when the case of US versus Shonubi was brought to his attention. Shonubi was a Nigerian working in New York. He was arrested at Kennedy Airport when seen behaving in a suspicious manner in the baggage hall, having returned on a flight from Nigeria. He was found to have 103 bags of a white substance inside him, four of which were examined. The white substance was identified as heroin. Shonubi was arrested, tried and found guilty of drug smuggling. The question then arose as to the length of sentence he should be given.     

Experience-weighted Attraction Learning in Normal Form Games

In ‘experience-weighted attraction’ (EWA) learning, strategies have attractions that reflect initial predispositions, are updated based on payoff experience, and determine choice probabilities according to some rule (e.g., logit). A key feature is a parameter δ that weights the strength of hypothetical reinforcement of strategies that were not chosen according to the payoff they would have yielded, relative to reinforcement of chosen strategies according to received payoffs. The other key features are two discount rates, φ and ρ, which separately discount previous attractions, and an experience weight. EWA includes reinforcement learning and weighted fictitious play (belief learning) as special cases, and hybridizes their key elements. When δ= 0 and ρ= 0, cumulative choice reinforcement results. When δ= 1 and ρ=φ, levels of reinforcement of strategies are exactly the same as expected payoffs given weighted fictitious play beliefs. Using three sets of experimental data, parameter estimates of the model were calibrated on part of the data and used to predict a holdout sample. Estimates of δ are generally around .50, φ around .8 − 1, and ρ varies from 0 to φ. Reinforcement and belief-learning special cases are generally rejected in favor of EWA, though belief models do better in some constant-sum games. EWA is able to combine the best features of previous approaches, allowing attractions to begin and grow flexibly as choice reinforcement does, but reinforcing unchosen strategies substantially as belief-based models implicitly do.     

Infant Symbolic Play as an Early Indicator of Fetal Alcohol‐Related Deficit

Infant symbolic play was examined in relation to prenatal alcohol exposure and socioenvironmental background and to predict which infants met criteria for fetal alcohol syndrome (FAS) at 5 years. A total of 107 Cape‐Colored, South African infants born to heavy drinking mothers and abstainers/light drinkers were recruited prenatally. Complexity of play, sociodemographic and psychological correlates of maternal alcohol use, and quality of parenting were assessed at 13 months, and intelligence quotient and FAS diagnosis at 5 years. The effect of drinking on spontaneous play was not significant after control for social environment. In contrast, prenatal alcohol and quality of parenting related independently to elicited play. Elicited play predicted 5‐year Digit Span and was poorer in infants subsequently diagnosed with FAS/partial FAS and in nonsyndromal heavily exposed infants, compared with abstainers/light drinkers. Thus, symbolic play may provide an early indicator of risk for alcohol‐related deficits. The independent effects of prenatal alcohol and quality of parenting suggest that infants whose symbolic play is adversely affected by alcohol exposure may benefit from stimulation from a responsive caregiver.     

Isomorphism,Institutional Parochialism,and the Sociology of Religion

This article investigates whether the field of sociology of religion is occupied by parochial concerns. We characterize institutional parochialism as the degree to which people in an academic field tend to study their own societies. This study employs a content analysis of articles published in The Journal for the Scientific Study of Religion and Sociology of Religion from 2001 to 2008, with particular attention paid to the incidences in which Muslim and non-Western groups were studied before and after the 9/11 terrorist attacks. There was no change in the rate that “Muslim” communities were studied following the 9/11 attacks, but it appears journal content did change to reflect ongoing debates in the West and in response to mimetic pressures being placed on the field. Overall, if the sociology of religion can be characterized as parochial, we contend that the broader field of American sociology is likely far more so.     

Creating caring institutions for community informatics

This paper explores the potential affordances of applying a feminist ethics of care approach to community informatics practices in public internet access facilities. As feminist technology scholars have long observed, technology and technoculture are strongly encoded as masculine, privileging traits such as scientific knowledge, rationality, objectivity, and distance. These characteristics are expressed in traditional infomediary practices in a variety of ways, including notions of expertise, ways of conceptualizing technology, emphasis on skills attainment, and deficit-based models of user behavior. In contrast, ethics of care emphasizes the importance of relational and situated knowledge, pluralistic voices and experiences, and relationships bound by mutual interdependence. Traditionally, caring has been feminized and thus necessarily excluded from technoculture and relegated to invisible and unpaid labor. Caring and associated affective labor practices remain an under-examined subject in infomediary practices. Public libraries and community technology centers are logical places to explore for care work, given that they share many characteristics of the spaces where care work has historically been performed. We argue that an ethics of care framework has several possible affordances for infomediary practices in these institutions, including highlighting the gendered power dynamics that define and shape existing practices; distributing care work and making existing care work visible; and envisioning a more holistic and ethical approach to engaging diverse publics. We translate Tronto’s seven warning signs for ‘bad care’ in institutions into seven positive guidelines for providing ‘good care’ in public internet access facilities, then contextualize these for community informatics institutions and practices.     

Automatic Bayesian quantile regression curve fitting

Quantile regression, including median regression, as a more completed statistical model than mean regression, is now well known with its wide spread applications. Bayesian inference on quantile regression or Bayesian quantile regression has attracted much interest recently. Most of the existing researches in Bayesian quantile regression focus on parametric quantile regression, though there are discussions on different ways of modeling the model error by a parametric distribution named asymmetric Laplace distribution or by a nonparametric alternative named scale mixture asymmetric Laplace distribution. This paper discusses Bayesian inference for nonparametric quantile regression. This general approach fits quantile regression curves using piecewise polynomial functions with an unknown number of knots at unknown locations, all treated as parameters to be inferred through reversible jump Markov chain Monte Carlo (RJMCMC) of Green (Biometrika 82:711–732, 1995). Instead of drawing samples from the posterior, we use regression quantiles to create Markov chains for the estimation of the quantile curves. We also use approximate Bayesian factor in the inference. This method extends the work in automatic Bayesian mean curve fitting to quantile regression. Numerical results show that this Bayesian quantile smoothing technique is competitive with quantile regression/smoothing splines of He and Ng (Comput. Stat. 14:315–337, 1999) and P-splines (penalized splines) of Eilers and de Menezes (Bioinformatics 21(7):1146–1153, 2005).