Coalition for a Healthier Community: Lessons learned and implications for future work

The Coalition for a Healthier Community (CHC) initiative was implemented to improve the health and well-being of women and girls. Underpinning CHC is a gender-based focus that uses a network of community partners working collaboratively to generate relevant behavior change and improved health outcomes. Ten programs are trying to determine whether gender-focused system approaches are cost-effective ways to address health disparities in women and girls. Programs implemented through coalitions made up of academic institutions, public health departments, community-based organizations, and local, regional, and national organizations, are addressing health issues such as domestic violence, cardiovascular disease prevention, physical activity, and healthy eating. Although these programs are ongoing, they have made significant progress. Key factors contributing to their early success include a comprehensive needs assessment, robust coalitions, the diversity of populations targeted, programs based on findings of the needs assessments, evaluations taking into consideration the effect of gender, and strong academic–community partnerships. A noteworthy impact of these programs has been their ability to shape and impact public, social, and health policies at the state and local levels. However, there have been challenges associated with the implementation of such a complex program. Lessons learned are discussed in this paper.     

An approximation of logarithmic functions in the regression setting

We consider a method of moments approach for dealing with censoring at zero for data expressed in levels when researchers would like to take logarithms. A Box–Cox transformation is employed. We explore this approach in the context of linear regression where both dependent and independent variables are censored. We contrast this method to two others, (1) dropping records of data containing censored values and (2) assuming normality for censored observations and the residuals in the model. Across the methods considered, where researchers are interested primarily in the slope parameter, estimation bias is consistently reduced using the method of moments approach.     

Beyond tail median and conditional tail expectation: Extreme risk estimation using tail Lp-optimization

The conditional tail expectation (CTE) is an indicator of tail behavior that takes into account both the frequency and magnitude of a tail event. However, the asymptotic normality of its empirical estimator requires that the underlying distribution possess a finite variance; this can be a strong restriction in actuarial and financial applications. A valuable alternative is the median shortfall (MS), although it only gives information about the frequency of a tail event. We construct a class of tail L^p-medians encompassing the MS and CTE. For p in (1,2), a tail L^p-median depends on both the frequency and magnitude of tail events, and its empirical estimator is, within the range of the data, asymptotically normal under a condition weaker than a finite variance. We extrapolate this estimator and another technique to extreme levels using the heavy-tailed framework. The estimators are showcased on a simulation study and on real fire insurance data.     

国外教师期望效应研究进展与当代教育启示

教师期望效应是教师对学生的期望在学生的未来发展中得到证实的现象,它反映了教师对学生的态度会影响学生发展的方向和程度,开展该现象的研究对教师观念的改变和学生的健康发展均有重要意义。对教师期望效应的种类、理论模型及国外的相关研究进行了介绍,探讨了其对教育现实的一些重要启示。     

Factor analysis for ranked data with application to a job selection attitude survey

Summary.  Factor analysis is a powerful tool to identify the common characteristics among a set of variables that are measured on a continuous scale. In the context of factor analysis for non-continuous-type data, most applications are restricted to item response data only. We extend the factor model to accommodate ranked data. The Monte Carlo expectation–maximization algorithm is used for parameter estimation at which the E-step is implemented via the Gibbs sampler. An analysis based on both complete and incomplete ranked data (e.g. rank the top q out of k items) is considered. Estimation of the factor scores is also discussed. The method proposed is applied to analyse a set of incomplete ranked data that were obtained from a survey that was carried out in GuangZhou, a major city in mainland China, to investigate the factors affecting people's attitude towards choosing jobs.     

关注公众预期提高货币供应量对经济的作用

对货币供应量与经济增长之间的关系以及货币供应机制进行了分析，据此得出结论：货币供应量在短期内可影响一国经济，所以控制货币供应量是调节经济的手段之一。但是由于影响货币供应量的因素不易控制和预测，使得货币供应量的控制和对经济的调节变得困难。所以应考虑引入预期指标来提高货币供应量调节经济的效果。     

论资本质量与财务目标

从传统财务目标的缺陷在于忽视资本质量的分析入手 ,论述了资本质量是资本的内在规定性 ,是资本社会属性的总和与资本经济属性的质量方面 ;将资本质量引入财务目标是由资本的本质和财务的本质、资本质量与资本数量之间的关系、时代特征和国家财务所决定的 ,资本质量最优化与资本数量最大化是财务目标的必然选择 ;提出了资本质量考核指标体系。     

和谐语境中的司法期待

法律关系是人际关系的特殊表现,当事人之间纠纷的发生导致了人际关系的破坏,法律的正义观应关注未来的人际关系。现实中被设计出来作为化解冲突、实现和谐的司法制度,却往往在实际的案件裁判中更多的成为延续和引发再次冲突的根源。因此,司法必须通过裁判使当事人从内心消除怨恨,实现人际关系的修复,而不是仅仅着眼于一个具体个案的审结。简单的追求效率不是以人为本的司法,也不符合转型社会的实际需要。