‘Are we to become a gender university?’ Facets of resistance to a gender equality project

Gender equality (GE) is something ‘we cannot not want’. Indeed, the pursuit of equal rights, responsibilities and opportunities for all women and men throughout a society freed from gendered oppression is widely visible in recent organizational GE initiatives. In practice, however, GE initiatives often fail in challenging gendered norms and at effecting deep‐seated change. In fact, GE measures tend to encounter resistance, with a gap between saying and doing. Using a GE project at a Swedish university, we examined the changing nature of reactions to GE objectives seeking to understand why gender inequality persists in academia. We used ‘resistance’ to identify multiple, complex reactions to the project, focusing on the discursive practices of GE. Focusing our contextual analysis on change and changes in reactions enabled a process‐oriented analysis that revealed gaps where change is possible. Thus, we argue that studying change makes it possible to identify points in time where gendered discriminatory norms are more likely to occur. However, analysing discursive practices does not itself lead to change nor to action. Rather, demands for change must start with answering, in a collaborative way, what problem we are trying to solve when we start a new GE project, in order to be relevant to the specific context. Otherwise, GE risks being the captive of consensus politics and gender inequality will persist.     

A simple two-stage design for quantitative responses with application to a study in diabetic neuropathic pain

Two-stage designs offer substantial advantages for early phase II studies. The interim analysis following the first stage allows the study to be stopped for futility, or more positively, it might lead to early progression to the trials needed for late phase II and phase III. If the study is to continue to its second stage, then there is an opportunity for a revision of the total sample size. Two-stage designs have been implemented widely in oncology studies in which there is a single treatment arm and patient responses are binary. In this paper the case of two-arm comparative studies in which responses are quantitative is considered. This setting is common in therapeutic areas other than oncology. It will be assumed that observations are normally distributed, but that there is some doubt concerning their standard deviation, motivating the need for sample size review. The work reported has been motivated by a study in diabetic neuropathic pain, and the development of the design for that trial is described in detail.     

The generalized log-gamma mixture model with covariates: local influence and residual analysis

In a sample of censored survival times, the presence of an immune proportion of individuals who are not subject to death, failure or relapse, may be indicated by a relatively high number of individuals with large censored survival times. In this paper the generalized log-gamma model is modified for the possibility that long-term survivors may be present in the data. The model attempts to separately estimate the effects of covariates on the surviving fraction, that is, the proportion of the population for which the event never occurs. The logistic function is used for the regression model of the surviving fraction. Inference for the model parameters is considered via maximum likelihood. Some influence methods, such as the local influence and total local influence of an individual are derived, analyzed and discussed. Finally, a data set from the medical area is analyzed under the log-gamma generalized mixture model. A residual analysis is performed in order to select an appropriate model. The authors would like to thank the editor and referees for their helpful comments. This work was supported by CNPq, Brazil.     

Testing structural breaks versus long memory with the Box–Pierce statistics: a Monte Carlo study

Several studies have found that occasional-break processes may produce realizations with slowly decaying autocorrelations, which is hardly distinguished from the long memory phenomenon. In this paper we suggest the use of the Box–Pierce statistics to discriminate long memory and occasional-break processes. We conduct an extensive Monte Carlo experiment to examine the finite sample properties of the Box–Pierce and other simple tests statistics in this framework. The results allow us to infer important guidelines for applied statistics in practice.     

A copula-based Markov chain model for the analysis of binary longitudinal data

A fully parametric first-order autoregressive (AR(1)) model is proposed to analyse binary longitudinal data. By using a discretized version of a copula, the modelling approach allows one to construct separate models for the marginal response and for the dependence between adjacent responses. In particular, the transition model that is focused on discretizes the Gaussian copula in such a way that the marginal is a Bernoulli distribution. A probit link is used to take into account concomitant information in the behaviour of the underlying marginal distribution. Fixed and time-varying covariates can be included in the model. The method is simple and is a natural extension of the AR(1) model for Gaussian series. Since the approach put forward is likelihood-based, it allows interpretations and inferences to be made that are not possible with semi-parametric approaches such as those based on generalized estimating equations. Data from a study designed to reduce the exposure of children to the sun are used to illustrate the methods.     

Bayesian robustness of the compound Poisson distribution under bidimensional prior: an application to the collective risk model

The distribution of the aggregate claims in one year plays an important role in Actuarial Statistics for computing, for example, insurance premiums when both the number and size of the claims must be implemented into the model. When the number of claims follows a Poisson distribution the aggregated distribution is called the compound Poisson distribution. In this article we assume that the claim size follows an exponential distribution and later we make an extensive study of this model by assuming a bidimensional prior distribution for the parameters of the Poisson and exponential distribution with marginal gamma. This study carries us to obtain expressions for net premiums, marginal and posterior distributions in terms of some well-known special functions used in statistics. Later, a Bayesian robustness study of this model is made. Bayesian robustness on bidimensional models was deeply treated in the 1990s, producing numerous results, but few applications dealing with this problem can be found in the literature.     

Variations in Citizenship Profiling by Generational Status: Individual and Neighborhood Characteristics of Latina/os Questioned by Law Enforcement About Their Legal Status

Although racial profiling is widely studied, the related issue of citizenship profiling by law enforcement has received little scholarly attention. In this study we begin to address citizenship profiling, which may be highly salient in light of the increasing policing of immigration in the United States through Secure Communities and other federal, state and local efforts to localize the enforcement of immigration laws. Using a sample of 563 Latina/o adults residing in 46 neighborhoods in El Paso County, Texas, USA, we assess the impacts of a variety of individual and neighborhood characteristics on the likelihood of being questioned about citizenship status by law enforcement. Results using hierarchical generalized linear models (HGLMs) show that, at the individual-level, first-generation Latina/o immigrants and second-Latina/os are more likely to be questioned about citizenship status than third- and later-generation Latina/os. At the neighborhood-level, living in a neighborhood with a mid-level of Latina/o immigrant characteristics increased the probability of being questioned. The implications of these findings for citizenship profiling are discussed.     

风险社会背景下大学生的信仰危机

当今,世界正由工业社会向风险社会过渡,信仰危机是当代人类面临的全球性问题,信仰危机的出现要求我们关注信仰教育。受全球化的影响,中国也处于风险社会之中。大学生作为我国社会主义事业的接班人,其信仰状况直接关系到国家的前途和命运。本文首先阐述了信仰以及信仰危机的含义,然后分析了我国大学生当前存在的信仰危机及其产生的原因,最后对于解决我国大学生的信仰危机提出了几点建议。     

The importance of being mature: the effect of demographic maturation on global per capita GDP

Given that savings behaviour and worker productivity have strong life-cycle components and given that demographic profiles vary across countries, population age structure should be linked to differences in levels of economic development. In this paper, we measure the economic importance of age structure variation for the global economy. We find that demographic maturation has been associated with nearly half of the evolution of global per capita GDP since 1960. We also find that age structure differences can account for just over half of the variation in worldwide per capita GDP (i.e. the lack of sigma convergence) observed since 1960.

Activism among older women in Quebec, Canada: changing the world after age 65

The aim of this article is to examine senior women's involvement experience in Quebec, Canada. Study results are based on a qualitative methodology, and shed light on family history and continuity in the involvement trajectory, diversity in terms of group type and involvement practices, and gender differences in involvement. The meaning that older women attribute to their involvement is also addressed, including attitudes toward feminism. The discussion highlights the extent to which older women's involvement has been marked by their life trajectories, above and beyond their age. In sum, their involvement in the private and public spheres is quite impressive.