Girls’ Jobs for the Boys? Men,Masculinity and Non‐Traditional Occupations

Occupational segregation by sex remains the most pervasive aspect of the labour market. In the past, most research on this topic has concentrated on explanations of women’s segregation into low paid and low status occupations, or investigations of women who have crossed gender boundaries into men’s jobs, and the potential impact on them and the occupations. In contrast, this article reports on a small‐scale, qualitative study of ten men who have crossed into what are generally defined as ‘women’s jobs’. In doing so, one of the impacts on them has been that they have experienced challenges to their masculine identity from various sources and in a variety of ways. The men’s reactions to these challenges, and their strategies for developing and accommodating their masculinity in light of these challenges, are illuminating. They either attempted to maintain a traditional masculinity by distancing themselves from female colleagues, and/or partially (re)constructed a different masculinity by identifying with their non‐traditional occupations. This they did as often as they deemed necessary as a response to different forms of challenge to their gender identities from both men and women. Finally, the article argues that these responses work to maintain the men as the dominant gender, even in these traditionally defined ‘women’s jobs’.     

企业现行分配制度的问题及改革

文章指出了企业现行分配制度存在的问题,阐述了岗效工资的运行机制,提出了岗效工资是企业分配制度改革的方向。     

Bayesian validation assessment of multivariate computational models

Multivariate model validation is a complex decision-making problem involving comparison of multiple correlated quantities, based upon the available information and prior knowledge. This paper presents a Bayesian risk-based decision method for validation assessment of multivariate predictive models under uncertainty. A generalized likelihood ratio is derived as a quantitative validation metric based on Bayes’ theorem and Gaussian distribution assumption of errors between validation data and model prediction. The multivariate model is then assessed based on the comparison of the likelihood ratio with a Bayesian decision threshold, a function of the decision costs and prior of each hypothesis. The probability density function of the likelihood ratio is constructed using the statistics of multiple response quantities and Monte Carlo simulation. The proposed methodology is implemented in the validation of a transient heat conduction model, using a multivariate data set from experiments. The Bayesian methodology provides a quantitative approach to facilitate rational decisions in multivariate model assessment under uncertainty.     

Bayesian analysis of directed graphs data with applications to social networks

Summary.  A fully Bayesian analysis of directed graphs, with particular emphasis on applica- tions in social networks, is explored. The model is capable of incorporating the effects of covariates, within and between block ties and multiple responses. Inference is straightforward by using software that is based on Markov chain Monte Carlo methods. Examples are provided which highlight the variety of data sets that can be entertained and the ease with which they can be analysed.     

A regression-based smoothing spline Monte Carlo algorithm for pricing American options in discrete time

American options in discrete time can be priced by solving optimal stopping problems. This can be done by computing so-called continuation values, which we represent as regression functions defined recursively by using the continuation values of the next time step. We use Monte Carlo to generate data, and then we apply smoothing spline regression estimates to estimate the continuation values from these data. All parameters of the estimate are chosen data dependent. We present results concerning consistency and the estimates’ rate of convergence.     

Optimal sampling for repeated binary measurements

The authors consider the optimal design of sampling schedules for binary sequence data. They propose an approach which allows a variety of goals to be reflected in the utility function by including deterministic sampling cost, a term related to prediction, and if relevant, a term related to learning about a treatment effect To this end, they use a nonparametric probability model relying on a minimal number of assumptions. They show how their assumption of partial exchangeability for the binary sequence of data allows the sampling distribution to be written as a mixture of homogeneous Markov chains of order k. The implementation follows the approach of Quintana & Müller (2004), which uses a Dirichlet process prior for the mixture.     

入世对中国传统文化的冲击与对策

如今中国加入世贸组织 ,中外文化在一种更加复杂和多元化的时代更深入地“亲密接触”已是有目共睹的事实 ,不同文化之间的相互影响、渗透甚至融合十分必要。因此 ,入世后中国传统文化究竟如何实现面向世界、面向未来、面向现代化的转变是我们急待解决的问题。解决这个问题的最佳解决方案是既应中西融会 ,但更要立足本土。     

谁开创了贝叶斯学派？——对拉普拉斯1774年一篇文章的回顾

1764年,贝叶斯的遗作《机遇理论中一个问题的解》，是当今统计学界贝叶斯学派的开山之作，然而直到20世纪，贝叶斯的文章却并未对后世贝叶斯学派的发展产生重大影响。事实上，真正促使贝叶斯的思想在科学界得到广泛传播的关键人物是大科学家拉普拉斯。1774年，拉普拉斯发表的关于贝叶斯理论的里程碑式的文章，使现代读者充分认识到拉普拉斯对贝叶斯学派发展所起的巨大作用，并从拉普拉斯的思想中获得了有益的新知。     

Bayesian analysis of elapsed times in continuous‐time Markov chains

The authors consider Bayesian analysis for continuous‐time Markov chain models based on a conditional reference prior. For such models, inference of the elapsed time between chain observations depends heavily on the rate of decay of the prior as the elapsed time increases. Moreover, improper priors on the elapsed time may lead to improper posterior distributions. In addition, an infinitesimal rate matrix also characterizes this class of models. Experts often have good prior knowledge about the parameters of this matrix. The authors show that the use of a proper prior for the rate matrix parameters together with the conditional reference prior for the elapsed time yields a proper posterior distribution. The authors also demonstrate that, when compared to analyses based on priors previously proposed in the literature, a Bayesian analysis on the elapsed time based on the conditional reference prior possesses better frequentist properties. The type of prior thus represents a better default prior choice for estimation software.     

网络环境下的研究性学习

利用网络开展研究性学习具有很大的优势,探讨网络研究性学习能力的培养、组织与实施,以及网络研究性学习的评价对提高学生的综合素质有重要作用。