Opinions toward suicide: Cross-national evaluation of cultural and religious effects on individuals

This study evaluates the role that religious and cultural values have on individual opinions toward suicide worldwide. Using multilevel modeling with data from the fourth wave of the World Values Survey (42,299 individuals in 43 countries), the current study is designed to analyze the effect of individual (i.e., micro-level), and country (i.e., macro-level) characteristics on opinions toward suicide. Specifically, cultural values, religious affiliation, religious importance, and church attendance are analyzed at both the individual and country levels to evaluate the impact of individual and country level effects on opinions toward suicide. The results show that individual opinions toward suicide are influenced by individual belief as well as by the cultural and religious characteristics of their country. The results suggest that evaluation of individual opinions toward controversial behavior should account for the unique and cross-interaction effects of micro- and macro-level effects.     

Wrapping and Unwrapping Emotions: Clinical Practice with East Asian Immigrant Elders

Using the cultural norm of the way gifts are wrapped, unwrapped, and exchanged as a metaphor for interpersonal connections, this paper presents the way therapists can establish therapeutic relationships with East Asian clients who do not express emotions openly. We first discuss the ways in which emotions are conceptualized, experienced, and expressed in East Asian cultures. We then present vignettes of our work with older Chinese and Japanese immigrant women to illustrate the importance of therapist authenticity and co-construction of the therapeutic relationship. Using the framework of relational/cultural theory, which posits that healing takes place in the context of mutually empathic growth-fostering relationships, we illustrate the importance of establishing mutuality between therapist and client as a form of cultural empathy.     

澳洲台湾移民居住地选择的初探

本文针对悉尼和布里斯本两个都市之台湾移民的分布及居住迁徙作深入研究。主要透过深入访谈的方法 ,系统性的针对台湾移民选择居住地的因子及决策过程进行探讨 ,并尽量以社会地理学“局内人”的观点 ,架构居住地改变和选择的逻辑来思考整个迁徙过程的机制。研究结果显示 ,随着时间的改变 ,作迁徙决策时所考量的因子也会改变。刚到澳洲时 ,选择居住地的因子主要会考量亲友意见 ;随着经验的累积及对周遭环境的熟悉 ,个别差异性开始凸显 ,每个人对居住地的选择会有不同的考量与分析。在迁居上 ,有向双拼式建筑或都市公寓型房子搬迁的趋势     

中美家庭结构与功能的比较分析

本研究聚焦于中美家庭结构和功能的异同以及文化力量的影响,利用美国社会工作学生访华计划设计了本研究课题,在中美双方老师的共同督导下,9名美国社会工作学生和18名中国社会工作学生参与了本课题研究,采用了面对面的深度访谈和观察的方法.比较了中美家庭在家庭结构、家庭决策、家庭沟通及家庭观念等方面的异同,并探讨了其中的文化影响力和对社会工作介入的启示.     

Unequal Regionalism: Regional Planning in China and England

This paper responds to the revival of regionalism in the past two decades by showing that such a re-emergence is unequal. Comparing the practice of regional planning in China and England, this paper has demonstrated that the party-state in China and the liberal-democratic state in England have responded differently to this revival and developed different framework for regional administration and planning. These variations have not only elaborated planners' concern about planning practice in a ‘context of difference’ from social dimension to geographical variations, but also echoed geographers' affirmation that global trends take on different characters in local setting.     

Hypergamy Among South Korean Women and Its Implications for the Marriage Rate

Population Research and Policy Review - This study aims to examine how income-based hypergamy among South Korean women affects the marriage rate. In a society that continues to practice income...     

Employment and earnings of foreign-born scientists and engineers

Population Research and Policy Review -     

Bayesian approach to estimation of intraclass correlation using reference prior

For the balanced variance component model when the intraclass correlation coefficient is of interest, Bayesian analysis is often appropriate. Berger and Bernardo’s (1992a) grouped ordering reference prior approach is used to analyze this model. The reference priors are developed and compared for the posterior inference with real and simulated data. We examine whether the reference priors satisfy the probability-matching criterion. Further, the reference prior is shown to be good in the sense of correct frequentist coverage probability of the posterior quantile.     

A Pilot for Improving Depression Care on College Campuses: Results of the College Breakthrough Series–Depression (CBS-D) Project

Abstract

Objective: To implement a pilot quality improvement project for depression identification and treatment in college health. Participants: Eight college health center teams composed primarily of primary care and counseling service directors and clinicians. Methods: Chronic (Collaborative) Care Model (CCM) used with standardized screening to identify, treat, and track depressed students for 12 weeks to monitor predetermined process and clinical outcomes. Results: Of all students receiving primary medical care services between January 2007 and May 2008, 69% (n = 71,908) were screened for depression. A total of 801 depressed students were treated and tracked; most predetermined treatment process and clinical outcome targets were achieved. Conclusion: The CCM for depression shows promise for improving depression identification and care for college students.     

A tutorial on rank-based coefficient estimation for censored data in small- and large-scale problems

The analysis of survival endpoints subject to right-censoring is an important research area in statistics, particularly among econometricians and biostatisticians. The two most popular semiparametric models are the proportional hazards model and the accelerated failure time (AFT) model. Rank-based estimation in the AFT model is computationally challenging due to optimization of a non-smooth loss function. Previous work has shown that rank-based estimators may be written as solutions to linear programming (LP) problems. However, the size of the LP problem is O(n ²+p) subject to n ² linear constraints, where n denotes sample size and p denotes the dimension of parameters. As n and/or p increases, the feasibility of such solution in practice becomes questionable. Among data mining and statistical learning enthusiasts, there is interest in extending ordinary regression coefficient estimators for low-dimensions into high-dimensional data mining tools through regularization. Applying this recipe to rank-based coefficient estimators leads to formidable optimization problems which may be avoided through smooth approximations to non-smooth functions. We review smooth approximations and quasi-Newton methods for rank-based estimation in AFT models. The computational cost of our method is substantially smaller than the corresponding LP problem and can be applied to small- or large-scale problems similarly. The algorithm described here allows one to couple rank-based estimation for censored data with virtually any regularization and is exemplified through four case studies.