Children's gender- and age-based categorization in similarity and induction tasks

The present studies examined children's and adults' preferences for gender- or age-based categorization using similarity and inductive inference tasks. Four-year-olds, 6-year-olds, and adults looked at pictures of people and decided which of two was more like a target (similarity condition) or which shared a novel age- or gender-related property with the target (inference condition). Age or gender-based matches were possible. The results are consistent with previous findings that gender-based classification decreases with age. However, they also demonstrate that children use gender more for judging similarity than for making inferences about novel properties. Distinct patterns emerge from the two tasks: 6-year-olds and adults in both conditions categorize more by age than gender; 4-year-olds categorize by gender more than age in the similarity task, but by age more in the induction task. Only adults differentiated by property in the inference condition. These findings suggest that the salience of gender categories cannot entirely be attributed to their inductive potential. Gender has a salience beyond what would be predicted by its power for directing novel generalizations.     

Older disabled workers' perceptions of volunteering

The activity of volunteering is readily available to, and undertaken by, able-bodied people in Australia and is recognized as a valuable social pursuit, particularly among citizens of retirement age. Despite the known benefits of volunteering, however, there are few reports of disabled people participating as volunteers and little is understood of their experiences or perceptions of volunteering. The aim of this study was to explore how older workers within supported employment settings perceived the opportunities for and barriers to volunteering. Fourteen people with long-standing impairments participated in this small qualitative study. Overall the participants were positive about volunteering, but noted they might require support to volunteer successfully. Drawing upon the participants' views, recommendations are made for developing training. Disabled workers facing retirement need to be supported to have opportunities for active participation in the community as volunteers if so desired.     

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.     

Population constraints on pooled surveys in demographic hazard modeling

In non-experimental research, data on the same population process may be collected simultaneously by more than one instrument. For example, in the present application, two sample surveys and a population birth registration system all collect observations on first births by age and year, while the two surveys additionally collect information on women’s education. To make maximum use of the three data sources, the survey data are pooled and the population data introduced as constraints in a logistic regression equation. Reductions in standard errors about the age and birth-cohort parameters of the regression equation in the order of three-quarters are obtained by introducing the population data as constraints. A halving of the standard errors about the education parameters is achieved by pooling observations from the larger survey dataset with those from the smaller survey. The percentage reduction in the standard errors through imposing population constraints is independent of the total survey sample size.