执政民主化建设的指导原则探略

本文指出加强执政民主化建设必须坚持自主性原则、渐进性原则、协调性原则和稳定性原则。     

基督教信仰的内在原则

基督教在寻求哲学的理解过程中,将促使理性自觉到哪些原则?或者说,在历史上,哲学从基督教信仰中化解出了什么样的原则?这一设问所要追寻的就是这里所说的基督教信仰的内在原则,亦即,那些借助于哲学的反思而可被理性所理解、因而内在于理性而可以从理性自身开显出来的原则。对基督教信仰的内在原则的分析表明,真正的宗教信仰与哲学这个被视为理性之典范的科学之间有着比人们想象的要复杂得多的关系它们之间一致的地方并不少于矛盾的地方。深刻的反思表明,对于哲学来说,基督教永远是一个有待进一步理解的信仰系统,就如哲学本身永远是一个开放的自由体系一样。     

公共服务的多元主体间互动机制分析

公共服务是公共服务的治理者、服务供应者、服务生产者、服务消费者四类主体之间的互动过程。本文通过对公共服务中主体角色的细分,探讨了公共服务过程中多元主体的互动关系。文章结合公共服务中的责任、权限、运行机制等制度安排以及与特定制度安排相适应的公共服务政策及工具体系,对我国公共服务的现状及将来的发展进行了研究。     

广东农村妇女妇女病检查影响因素及对策

妇女病不但危害育龄妇女的生殖健康,影响生命质量,还对家庭和谐幸福及社会整体健康水平带来负面影响。在农村妇女中开展妇科疾病定期检查是政府作为关注和保障民生、使广大妇女广泛而长久受惠的一项重要战略举措。因此,广东现行农村妇科病普查是否科学、合理,如何才能提高广大农村妇女妇科病的普查率,是政府十分关注的议题。     

Welfare Programme Participation and the Wellbeing of Non-local Rural Migrants in Metropolitan China: A Social Exclusion Perspective

Social Indicators Research - China has seen an unprecedented increase in rural-to-urban migrants in the last three decades, and the extension of welfare programmes to these migrants has been a...     

White and nonwhite trends in first birth timing: Comparisons using vital registration and current population surveys

The magnitude of racial differences in first birth timing vary greatly depending upon the data sources from which they are estimated. Vital registration data (Heuser 1976; with updates from the National Center for Health Statistics 1974–1990) show that in recent years nonwhites have higher risks of a first birth at virtually all ages compared to whites. As a result very large and historically novel differentials in childlessness are forecast using these data (see Rindfuss et al. 1988; Chen & Morgan 1991; Morgan & Chen 1992). However, retrospective fertility history data collected from the 1980, 1985 and 1990 Current Population Surveys (CPS) suggest much smaller racial differences in completed childlessness and isolate racial differences in probabilities of first births at young ages. Differences also exist between theses two series for whites prior to the mid-1960s but not afterwards. Reasons for these differing estimates are suggested and examined. We conclude that a substantial portion of the differences result from an accumulation of biases in the vital registration estimates that affect primarily estimates of first birth timing. Thus, the CPS data provide a more firm basis for racial comparisons of first birth timing.     

Glory May Not Be Achieved in Magnificence——Song Guangzhi and his printmaking

Admirable persistence I don ’t have much knowledge about printmaking. For Chinese printmaking, I even know much less. What I can get in my memory about printmaking are only     

Mixture regression models for the gap time distributions and illness–death processes

Lifetime Data Analysis - The aim of this study is to provide an analysis of gap event times under the illness–death model, where some subjects experience “illness” before...     

Majorization minimization by coordinate descent for concave penalized generalized linear models

Recent studies have demonstrated theoretical attractiveness of a class of concave penalties in variable selection, including the smoothly clipped absolute deviation and minimax concave penalties. The computation of the concave penalized solutions in high-dimensional models, however, is a difficult task. We propose a majorization minimization by coordinate descent (MMCD) algorithm for computing the concave penalized solutions in generalized linear models. In contrast to the existing algorithms that use local quadratic or local linear approximation to the penalty function, the MMCD seeks to majorize the negative log-likelihood by a quadratic loss, but does not use any approximation to the penalty. This strategy makes it possible to avoid the computation of a scaling factor in each update of the solutions, which improves the efficiency of coordinate descent. Under certain regularity conditions, we establish theoretical convergence property of the MMCD. We implement this algorithm for a penalized logistic regression model using the SCAD and MCP penalties. Simulation studies and a data example demonstrate that the MMCD works sufficiently fast for the penalized logistic regression in high-dimensional settings where the number of covariates is much larger than the sample size.