Tracking national and regional spatial-temporal mortality risk associated with NO2 concentrations in Canada: a Bayesian hierarchical two-level model

The association between daily variations in urban air quality and mortality has been well documented using time series statistical methods. This approach assumes a constant association over time. We develop a space-time dynamic model that relaxes this assumption, thus more directly examining the hypothesis that improvements in air quality translate into improvements in public health. We postulate a Bayesian hierarchical two-level model to estimate annual mortality risks at regional and national levels and to track both risk and heterogeneity of risk within and between regions over time. We illustrate our methods using daily nitrogen dioxide concentrations (NO2) and nonaccidental mortality data collected for 1984-2004 in 24 Canadian cities. Estimates of risk and heterogeneity are compared by cause of mortality (cardio-pulmonary [CP] versus non-CP) and season, respectively. Over the entire period, the NO2 risk for CP mortality was slightly lower but with a narrower credible interval than that for non-CP mortality, mainly due to an unusually low risk for a single year (1998). Warm season NO2 risk was higher than cold season risk for both CP and non-CP mortality. For 21 years overall there were no significant differences detected among the four regional NO2 risks. We found overall that there was no strong evidence for time trends in NO2 risk at national or regional levels. However, an increasing linear time trend in the annual between-region heterogeneities was detected, which suggests the differences in risk among the four regions are getting larger, and further studies are necessary to understand the increasing heterogeneity.     

The racial politics of STEM education in the USA: interrogations and explorations

ABSTRACT

This special issue brings together a mix of early-career, mid, and senior scholars to critically examine current realities of, and boldly imagine future possibilities for, STEM education in the lives of racially minoritized children in the United States. Given the implicit and sometimes explicit aspirations of STEM education to be a counteracting force against racialized injustice, how do students and communities of color experience and make sense of STEM reforms/initiatives? By examining a broad range of STEM contexts including mathematics, computer science, science and environmental science education, and through a diversity of methodological approaches, this special issue aims to contribute to a scholarly conversation about how racialized power intersects with the larger themes and foci of STEM education. In our introduction, we both highlight broad themes of the issue, and offer possible directions for future research at the intersections of race, power, and STEM.     

The influences of gender and grade on perceived work stress and job satisfaction in white collar employees

A self-completion questionnaire survey was carried out, resulting in a sample of 675 white collar public sector employees. The survey examined the frequency of occurrence of work-based stressors and perceived control, and included a general measure of job satisfaction. The results revealed that higher levels of job satisfaction were reported by employees in higher grades. It was also observed that higher grades perceived more control within their working environment. No gender differenccs were found concerning reported stress problems, although significant differences were observed across grades in relation to role differentiation. Multivariate analyses revealed that grade effects were largely accounted for by differences in perceived control. Perceived control, role-based and organizational stressors as well as gender were the strongest contributors in predicting reported job satisfaction.     

Product-limit survival functions with correlated survival times

A simple variance estimator for product-limit survival functions is demonstrated for survival times with nested errors. Such data arise whenever survival times are observed within clusters of related observations. Greenwood's formula, which assumes independent observations, is not appropriate in this situation. A robust variance estimator is developed using Taylor series linearized values and the between-cluster variance estimator commonly used in multi-stage sample surveys. A simulation study shows that the between-cluster variance estimator is approximately unbiased and yields confidence intervals that maintain the nominal level for several patterns of correlated survival times. The simulation study also shows that Greenwood's formula underestimates the variance when the survival times are positively correlated within a cluster and yields confidence intervals that are too narrow. Extension to life table methods is also discussed.     

Rich Ties and Innovative Knowledge Transfer within a Firm

We show that contacts in formal, informal and especially multiplex networks explain transfer of innovative knowledge in an organization. The contribution of informal contacts has been much acknowledged, while that of formal contacts did not receive much attention in the literature in recent decades. No study thus far has included both these different kinds of contacts in a firm, let alone considered their combined effect. The exact overlap between formal as well as informal contacts between individuals, forming multiplex or what we call rich ties because of their contribution, especially drives the transfer of new, innovative knowledge in a firm. Studying two cases in very different settings suggests these rich ties have a particularly strong effect on knowledge transfer in an organization, even when controlling for the strength of ties. Some of the effects on knowledge transfer in an organization previously ascribed to either the formal network or the informal network may actually be due to their combined effect in a rich tie.     

Addressing elder abuse: the Waterloo restorative justice approach to elder abuse project

The Community Care Access Centre (CCAC) of Waterloo Region, in partnership with a number of other social service agencies, designed and implemented a restorative justice model applicable to older adults who have been abused by an individual in a position of trust. The project was very successful in building partnerships, as many community agencies came together to deal with the problem of elder abuse. The program also raised the profile of elder abuse in the community. However, despite intensive efforts, referrals to the restorative justice program were quite low. Because of this, the program moved to a new organizational model, the Elder Abuse Response Team (EART), which has retained the guiding philosophy of restorative justice but has broadened the mandate. The team has evolved into a conflict management system that has multiple points of entry for cases and multiple options for dealing with elder abuse. The team has developed a broad range of community partners who can facilitate referrals to the EART and also can help to provide an individualized response to each case. The transition to the EART has been successful, and the number of referrals has increased significantly.     

Fitting Kent models to compositional data with small concentration

Compositional data can be transformed to directional data by the square root transformation and then modelled by using the Kent distribution. The current approach for estimating the parameters in the Kent model for compositional data relies on a large concentration assumption which assumes that the majority of the transformed data is not distributed too close to the boundaries of the positive orthant. When the data is distributed close to the boundaries with large variance significant folding may result. To treat this case we propose new estimators of the parameters derived based on the actual folded Kent distribution which are obtained via the EM algorithm. We show that these new estimators significantly reduce the bias in the current estimators when both the sample size and amount of folding is moderately large. We also propose using a saddlepoint density approximation for the Kent distribution normalising constant in order to more accurately estimate the shape parameters when the concentration is small or only moderately large.