School governing bodies: Reshaping education in their own image?

Recent educational reforms in England have given considerable responsibilities for the overall administration of schools to governing bodies largely comprised of lay people. The paper explores the knowledge of education possessed by lay governors. Issues considered include: the systematicity of that knowledge; its possible sources, and how gender, ethnicity and social class influence the knowledge held and used by governors. Also examined are the question of whether governors are always knowledgeable actors within the context of education and the implications of this for schools and democratic participation in their governance. Data is derived from a four year qualitative multi-site case study of ten school governing bodies in two English local education authorities undertaken by the authors between 1988 and 1992.     

THE LEAGUE OF NATIONS AND THE IRISH QUESTION:

This article builds on theoretical work in the social movements literature that uses "master frames" (Snow and Benford 1992) to account for the cyclical clustering of social movement activity within certain historical periods. I identify "master frame alignment" as the dynamic process by which social movement actors rhetorically transform the master frames within a cycle of protest to make them resonate more clearly with a movement's unique social and historical situation. Just as frame alignment processes serve to link a movement organization's activities, goals, and ideology with those of a potential group of adherents, master frame alignment processes link the activities, goals, and ideology of a movement organization with those espoused within the broader symbolic atmosphere of the social movement. I present historical data from Irish newspapers and political documents to show how the Irish Sinn Féin movement, seeking self-determination during the early twentieth century, rhetorically reconstructed the master frames generated by the League of Nations in order to better exploit this particular window of political opportunity.     

The current state of the labor queue: National and regional Evidence

We employ vector autoregressive techniques to determine the current state of the labor queue. Unemployment rate differentials have narrowed in recent years, potentially due to a change in the queue ordering, though a tight labor market and a stable queue would yield similar results. We find no evidence that the queue ordering has changed, which brings into question the resiliency of gains made by minority groups. We employ the same techniques to reveal the state of the queue across geographic regions and find that substantial differences exist across regions, implying variation in the relative labor force status of demographic groups.     

Bayesian analysis of a marked point process: Application in seismic hazard assessment

Point processes are the stochastic models most suitable for describing physical phenomena that appear at irregularly spaced times, such as the earthquakes. These processes are uniquely characterized by their conditional intensity, that is, by the probability that an event will occur in the infinitesimal interval (t, t+Δt), given the history of the process up tot. The seismic phenomenon displays different behaviours on different time and size scales; in particular, the occurrence of destructive shocks over some centuries in a seismogenic region may be explained by the elastic rebound theory. This theory has inspired the so-called stress release models: their conditional intensity translates the idea that an earthquake produces a sudden decrease in the amount of strain accumulated gradually over time along a fault, and the subsequent event occurs when the stress exceeds the strength of the medium. This study has a double objective: the formulation of these models in the Bayesian framework, and the assignment to each event of a mark, that is its magnitude, modelled through a distribution that depends at timet on the stress level accumulated up to that instant. The resulting parameter space is constrained and dependent on the data, complicating Bayesian computation and analysis. We have resorted to Monte Carlo methods to solve these problems.