Estimating the movement among staging areas of the barnacle goose ( Branta leucopsis )

Barnacle geese ( Branta leucopsis ) make annual migrations between breeding colonies in northern Europe and Eurasia to wintering grounds in Holland. During the migration, they sojourn for several weeks in five areas on the northern coast of Germany. Observers traverse these areas during the course of studying the flocks. Previous belief was that there was little exchange of birds among the five areas; however, some banded birds were observed in more than one area indicating that some movement takes place. In this presentation, we estimate the movement rates among the areas using open- and closed-population models.     

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.     

Use of Technology in Delivering Career Services Worldwide

The authors review the trends in the use of computers in the delivery and support of career guidance and counseling identified at the symposium International Perspectives on Career Development. The papers presented emphasized that 20th‐century computer‐based systems continue to be used, mainly delivered via the World Wide Web. These systems are enhanced through audio, video, graphics, strategies to provide needs assessment, and support by cybercounselors or expert system design. The papers also revealed a new trend: the use of elegant Web sites to store and search immense libraries of resources needed by professionals and clients and to facilitate communication and collaboration among professionals in cyberspace. Concerns, issues, and resources related to many areas, including the readiness of clients to use computer‐based systems, were also raised; existing sources of guidelines are noted.     

Factor analysis for ranked data with application to a job selection attitude survey

Summary.  Factor analysis is a powerful tool to identify the common characteristics among a set of variables that are measured on a continuous scale. In the context of factor analysis for non-continuous-type data, most applications are restricted to item response data only. We extend the factor model to accommodate ranked data. The Monte Carlo expectation–maximization algorithm is used for parameter estimation at which the E-step is implemented via the Gibbs sampler. An analysis based on both complete and incomplete ranked data (e.g. rank the top q out of k items) is considered. Estimation of the factor scores is also discussed. The method proposed is applied to analyse a set of incomplete ranked data that were obtained from a survey that was carried out in GuangZhou, a major city in mainland China, to investigate the factors affecting people's attitude towards choosing jobs.     

Gender,lineage, and fertility‐related outcomes in Ghana

A growing literature examines the empirical relationship between the joint reproductive preferences of marital partners and reproductive outcomes in Africa. Less explored is how spousal power in decision making may be influenced by lineage type. Using pooled data from Ghana, we investigate how lineage affects gendered reproductive decision outcomes and find some evidence that matrilineal women are more able than nonmatrilineal women to translate their reproductive preferences into action consistent with their goals.     

Discrete time modelling of disease incidence time series by using Markov chain Monte Carlo methods

Summary.  A stochastic discrete time version of the susceptible–infected–recovered model for infectious diseases is developed. Disease is transmitted within and between communities when infected and susceptible individuals interact. Markov chain Monte Carlo methods are used to make inference about these unobserved populations and the unknown parameters of interest. The algorithm is designed specifically for modelling time series of reported measles cases although it can be adapted for other infectious diseases with permanent immunity. The application to observed measles incidence series motivates extensions to incorporate age structure as well as spatial epidemic coupling between communities.