The social class of Catholics in Scotland

The social status of people brought up as Catholics in Scotland, as measured by their occupational class, is analysed by using cross-sectional survey data gathered in 1997. The main finding is that Catholics have probably risen in social status to a greater extent than non-Catholics. The experience of Scottish Catholics seems to be distinctive, because no such patterns are found for England, and indeed in this respect Scottish Catholics more closely resemble members of non-Christian religions in England than they do English Catholics. The most likely explanation is the particular role which state-funded Catholic schools have played in Scotland, especially the system of comprehensive secondary schools that was set up after 1965. However, the analysis is suggestive rather than definitive and needs to be replicated on cohort data with larger sample sizes.     

Coming Out and Coming Home

This paper draws on the testimonies of British disabled lesbians and gay men about their experience of coming out as gay, and coming out as disabled. They reflect on the different aspects of their identity, and the interrelation of their sexuality and their disability. The respondents share their experiences of exclusion and marginality in both the disability and gay communities, and discuss where they feel most at home as disabled lesbians and gays.     

A simple way to obtain the spectral decomposition of variance components models for balanced data

By means of an example it is shown how eigenvalues and eigenvectors of variance components models can be obtained straightforwardly when balanced data are available. Simple asymptotically efficient estimators of the variance components are presented.     

Who We Are Affects How We Do: The Financial Benefits of Organizational Identification

One ultimate test of the material value of identification in an organizational context is whether it relates to productivity. In this rare study of a business team in a global consumer goods company, we demonstrate a sales benefit of organizational identification when correcting for systematic between‐unit differences in sales. Findings also question the theoretical and practical meaning of ‘proximity’ in accounting for salience variations in identification – the best predictor of sales was the degree of identification with the superordinate business unit. Findings shed light on the scientific as well as managerial and business utility of the organizational identity concept.     

Bayesian inference for dynamic social network data

We consider a continuous-time model for the evolution of social networks. A social network is here conceived as a (di-) graph on a set of vertices, representing actors, and the changes of interest are creation and disappearance over time of (arcs) edges in the graph. Hence we model a collection of random edge indicators that are not, in general, independent. We explicitly model the interdependencies between edge indicators that arise from interaction between social entities. A Markov chain is defined in terms of an embedded chain with holding times and transition probabilities. Data are observed at fixed points in time and hence we are not able to observe the embedded chain directly. Introducing a prior distribution for the parameters we may implement an MCMC algorithm for exploring the posterior distribution of the parameters by simulating the evolution of the embedded process between observations.     

A Test to Detect Within-family Infectivity when the Whole Epidemic Process is Observed

An epidemic model for the spread of an infectious disease in a population of families is considered. The score test of the hypothesis that there is no higher infectivity between family members is constructed under the assumption that the epidemic process is observed continuously up to some time t . The score process is a martingale as a function of t and by letting the number of families tend to infinity, a central limit theorem for the process can be proved. The central limit theorem not only justifies a normal approximation of the test statistic—it also suggests a smaller variance estimator than expected.     

Bayesian point null hypothesis testing via the posterior likelihood ratio

This paper gives an exposition of the use of the posterior likelihood ratio for testing point null hypotheses in a fully Bayesian framework. Connections between the frequentist P-value and the posterior distribution of the likelihood ratio are used to interpret and calibrate P-values in a Bayesian context, and examples are given to show the use of simple posterior simulation methods to provide Bayesian tests of common hypotheses.     

Early Word Segmentation by Infants and Toddlers With Williams Syndrome

This study tested the ability of English infants and toddlers with Williams syndrome to segment, that is, to extract from fluent speech, bisyllabic nouns that had either a strong–‐weak stress pattern (predominant in English), or a weak–‐strong stress pattern. The testing procedure was the same for both types of words: Children were familiarized with instances of isolated nouns, and then tested on their recognition of these nouns embedded in passages. In English, typically developing infants start segmenting strong–‐weak nouns by 7.5 months of age, and weak–‐strong nouns by 10.5 months. Our clinical population was able to segment strong–‐weak nouns, but failed, despite chronological ages above 15 months, to segment weak–‐strong words. These results suggest that the development of word segmentation is seriously delayed in Williams syndrome. This deficit in early phonological processing may contribute to a fuller understanding of the late lexical onset in this population, a phenomenon that had hitherto only been explained in terms of cognitive and semantic deficits.