Gender and Power: Sex Segregation in American and Polish Higher Education as a Case Study

This article presents a comparative case study of the manifestation of sex segregation in higher education in the United States and in Poland from the end of the 19th century to the 1930s. The study is guided by a theoretical framework, which is organized around a concept of power and derived from The Sources of Social Power by Michael Mann (1986). In the United States, well-developed capitalism, democracy, and the ideology of separate spheres underlay the high collective power of men, their distributive power over women and—consequently—high levels of sex segregation in higher education. Contrastly, in Poland, weak capitalism and lack of democracy meant less collective and distributive power of men, which produced lower levels of educational sex segregation.     

Gender Differences in Perceived Disciplinary Fairness

This exploratory study coded and analysed 120 behaviours on videotaped data of 111 male and 30 female managers engaged in disciplinary discussions with one of their unionized employees. Four categories of behaviour were coded: non‐verbal communication, speech characteristics, leadership and interactional justice. A factor analysis of the results generated 14 factors, ten of which were correlated with experts’ ratings of disciplinary fairness. Female managers exhibited significantly higher levels of seven of the ten behavioural factors. Female managers also made more supportive interruptions than male managers and took more time for the disciplinary discussion, both of which were positively correlated with disciplinary fairness. The results suggest that leadership and communication styles commonly found in females may lead them to be better equipped than male managers to manage employee discipline situations.     

COMPONENTS OF VARIANCE MODELS WITH TRANSFORMATIONS

Power transformations are a popular way to improve the agreement between the observations and the assumptions in a statistical model. In this paper it is assumed that the data, after appropriate power transformation Λ, satisfies a variance components model, with independent Gaussian components. The focus is on inference for quantities which have an interpretation regardless of the choice of Λ (Carroll & Ruppert, 1981) – in particular the intraclass correlation coefficient ρ, the predicted probability of a new observation being less than a specified value and the predicted quantile. It is shown that, in the case Λ= 0, the asymptotic variance of ρ is the same, whether or not one treats Δ as estimated or as known. This supports an empirical conjecture of Solomon (1985). For predicted probabilities and predicted quantiles the variance when A is estimated is shown to be only slightly greater than the variance assuming Δ is known, except in the tails of the distribution where there can be substantial difference between the two variances.     

Urban politics and the study of urban poverty: Promising developments and future directions

The study of urban poverty is alive and well in sociology. The study of urban politics, by contrast, has stagnated. Though scholars agree that politics shapes the creation and durability of urban poverty, analytical connections between the two subfields are rarely made explicit. In this article, I make the case for a more integrated body of research. I first illustrate how urban poverty scholars implicitly discuss politics, and conversely, how urban politics scholars implicitly discuss poverty. I then highlight recent developments in the literature and propose two paths forward—by no means the only paths forward, but two ways to jumpstart greater conversation across both subfields. For the urban poverty literature, a focus on organizations can help scholars analyze political dynamics more directly. And for the urban politics literature, an emphasis on political mechanisms rather than overarching perspectives can disrupt the current theoretical malaise. These two moves can advance both literatures while drawing them closer together.     

Dirty money: Is there a wage premium for working in a pollution intensive industry?

Within a compensating wage differential framework we investigate whether there is a wage premium for working in a pollution intensive industry. Our results for the economy as a whole suggest a small wage premium of approximately one quarter of one percent associated with the risk of working in a dirty job. This premium rises to over fifteen percent for those individuals who work in one of the five dirtiest industries. We also find evidence of a fatal risk wage premium, providing estimates of the value of a statistical life of between ￡12 million and ￡19 million (2000 prices).     

Frame modifications with a dying client

Abstract

This paper explores the nature of the treatment frame with a client in extreme circumstances. A move is made, through frame alterations, from a more “pure” technical mode to a more humanistic one. The costs and gains of these frame modifications are evaluated and the therapist's internal experience of the process presented. The paper concludes that the traditional frame is inadequate in therapy with a dying client. Blending the customary frame with a more flexible one more fully meets the needs of the client who is in extremis, enhancing treatment and the treatment alliance.     

Quantifying the Economic Impact of Hydraulic Fracturing Proppant Selection in Light of Occupational Exposure Risk and Functional Requirements

Selection of an effective and economic proppant material for hydraulic fracturing is an important design choice to optimize the production of oil and natural gas. Proppants are made of silica (quartz sand), alumina, resin-coated silica, ceramics, and others. These materials can be toxic to varying degrees and lead to health problems in the employees handling them primarily due to inhalation exposure. Proppants are selected based on grain size, shape, strength, and cost. Current use is dominated by crystalline silica—the proppant that also has the greatest hazard as an inhalation toxin. Existing research describes the effect of silica on human health, but little research has been done to determine the risk-reduction and social-cost-effectiveness associated with using alternative proppants in light of the health risks. This study quantifies the relative risks or benefits to human health by the use of these proppants through an economic analysis considering the health-related economic impact and its technical attributes. Results show that the use of each ton of silica proppant results in $123 of external costs from fatalities and nonfatal illness arising due to exposure to silica for a crew handing 60,000 tons of proppants. If these health-related externalities were incorporated into the cost, silica proppant could be economically replaced by less harmful, more expensive alternatives for hydraulic fracturing crews handling less than 60,000 tons of proppant each year.     

Synthetic data method to incorporate external information into a current study

We consider the situation where there is a known regression model that can be used to predict an outcome, Y, from a set of predictor variables X . A new variable B is expected to enhance the prediction of Y. A dataset of size n containing Y, X and B is available, and the challenge is to build an improved model for Y| X ,B that uses both the available individual level data and some summary information obtained from the known model for Y| X . We propose a synthetic data approach, which consists of creating m additional synthetic data observations, and then analyzing the combined dataset of size n + m to estimate the parameters of the Y| X ,B model. This combined dataset of size n + m now has missing values of B for m of the observations, and is analyzed using methods that can handle missing data (e.g., multiple imputation). We present simulation studies and illustrate the method using data from the Prostate Cancer Prevention Trial. Though the synthetic data method is applicable to a general regression context, to provide some justification, we show in two special cases that the asymptotic variances of the parameter estimates in the Y| X ,B model are identical to those from an alternative constrained maximum likelihood estimation approach. This correspondence in special cases and the method's broad applicability makes it appealing for use across diverse scenarios. The Canadian Journal of Statistics 47: 580–603; 2019 © 2019 Statistical Society of Canada