Policy innovation and policy realisation: the example of children future education and development accounts in Taiwan

ABSTRACT

The Children Future Education and the Development Accounts (CFEDAs) are the first anti-poverty policy in Taiwan developed to provide incentives for the poor to accumulate assets for their future. Using CFEDAs as an example, this article analyses the process of developing and implementing an asset-based policy. It begins with an introduction to the policy structure. It then reviews the history of how the innovative idea of building assets for the poor became a policy proposal before presenting the convergence of three policy streams driving the prioritisation of CFEDAs in Taiwan’s policy agenda. It concludes with challenges facing the policy implementation.     

Do social work education,job description,and cultural competence foster child‐welfare caseworkers' therapeutic alliances?

We explored whether the strength of caseworkers' engagement with families in the child‐welfare system was associated with the caseworkers' academic degrees, job responsibilities and environments, and/or ethnicity. We extracted data from a national data set describing 1,714 caseworkers. Results confirmed significant association between caseworkers' confidence in their engagement with families and (a) master's‐ and bachelor's‐level social work education, (b) adequate supervision at work, (c) cultural‐diversity training, (d) job focus (screening/investigation, out‐of‐home placement, or reunification), and (e) homogeneous race/ethnicity of caseworker and client.     

基于元网络分析的重大基础设施建设项目风险评估框架与实证

重大基础设施项目具有战略性、集成性、复杂性等特征，项目容易受到多种风险因素的综合影响，导致项目目标的偏离。现有风险评估与风险决策的方法缺乏对于风险因素、风险事件之间关联的分析。为了实现重大基础设施建设项目综合系统的风险评估，本文采用元网络分析方法，构建项目目标、风险事件和风险因素的交互模型，揭示重大基础设施风险事件发生机制的黑箱过程。风险评估过程中，通过多个网络叠加运算分析每个风险因素对于各种风险事件以及项目各目标的影响情况，改进了以往仅对风险因素单一影响程度的风险评估方法。同时，本研究选择我国某河流水电站过坝运输项目方案比选的风险评估过程验证方法的适用性。     

我国普通高校高等教育成本分担主体探究

经过多年的实践,我国普通高校逐渐形成了以政府、学生及家长、高校及社会等主体共同分担的高等教育投入体制。近十五年来,我国普通高校政府分担的高等教育成本不断下降,学生及家长分担的成本持续上升,而高校与社会所分担的高等教育成本仍然较低。因此,我国的高等教育成本分担体制还有待于进一步完善。     

大数据时代"通过设计保护数据"的元规制

大数据时代,个人数据保护面临新的威胁和挑战,主要集中于数据收集、分析、使用等阶段."公平信息实践原则"作为个人数据保护的重要原则,难以有效应对大数据带来的挑战,尤其是"信息自我管理"理论和"告知-同意"工具出现失灵."通过设计保护数据"的基本主张是将个人数据保护纳入设备、产品或服务的设计过程,体现了"通过设计保护隐私"和"代码即法律"的理念,可以有效弥补个人数据保护和技术设计之间的差距,成为"公平信息实践原则"的重要补充.我国在未来的个人信息保护立法中,应当构建"通过设计保护数据"的元规制模式,将"通过设计保护数据"作为个人信息保护的基本原则,制定相应的技术标准,鼓励实施适当的认证机制,从外部刺激企业自我规制,强化"通过设计保护数据"的实施.     

Regression models with ordered multiple categorical predictors

Ordered multiple categorical (MC) variable has been widely considered and studied as response variable, and few studies have carefully considered it as a predictor in linear regression. When doing this, the existence of some pseudo-categories may result in overfitting, and to detect those pseudo-categories by hypothesis test of all dummy variables might have low specificity. In this paper, we propose a transformation method of dummy variables for such ordered MC predictors, after which a model selection method combined with BIC will be elaborated. Theoretical consistency of our model selection method is established under some common assumptions. Both simulation studies and real data analysis of a medical survey indicate that our method provides good performance and is applicable to a wide range of biomedical research.     

Propensity score prediction for electronic healthcare databases using super learner and high-dimensional propensity score methods

ABSTRACT

The optimal learner for prediction modeling varies depending on the underlying data-generating distribution. Super Learner (SL) is a generic ensemble learning algorithm that uses cross-validation to select among a ‘library’ of candidate prediction models. While SL has been widely studied in a number of settings, it has not been thoroughly evaluated in large electronic healthcare databases that are common in pharmacoepidemiology and comparative effectiveness research. In this study, we applied and evaluated the performance of SL in its ability to predict the propensity score (PS), the conditional probability of treatment assignment given baseline covariates, using three electronic healthcare databases. We considered a library of algorithms that consisted of both nonparametric and parametric models. We also proposed a novel strategy for prediction modeling that combines SL with the high-dimensional propensity score (hdPS) variable selection algorithm. Predictive performance was assessed using three metrics: the negative log-likelihood, area under the curve (AUC), and time complexity. Results showed that the best individual algorithm, in terms of predictive performance, varied across datasets. The SL was able to adapt to the given dataset and optimize predictive performance relative to any individual learner. Combining the SL with the hdPS was the most consistent prediction method and may be promising for PS estimation and prediction modeling in electronic healthcare databases.     

Ordering properties of largest order statistics from independent and heterogeneous Dagum populations

Abstract

The Dagum distribution has been extensively used to model income data, and its features have been appreciated in economics and financial studies. In this article, we discuss ordering properties of largest order statistics from independent and heterogeneous Dagum populations. We present some sufficient conditions for stochastic comparisons between largest order statistics in terms of the reversed hazard rate order, the usual stochastic order, the convex order, the likelihood ratio order and the dispersive order. Several numerical examples are presented to illustrate the results established here.     

欧盟跨国治理经验及对中国大都市圈治理的启示

推动都市圈建设是当今中国城市化发展和区域经济发展的主导战略.欧盟作为一个跨国政治经济联盟,也是区域一体化发展的典范,其成功的跨国治理体制机制促使商品、资金、服务、技术、人才等实现了跨国自由流动与重组.全面分析和借鉴欧盟跨国治理的成功经验,无疑对完善长江三角洲地区、京津冀、粤港澳大湾区等跨省都市圈的治理体系和促进经济高质量一体化发展具有重要意义.未来,可从加强顶层设计、完善促进大都市圈发展的法律法规,建立大都市圈双层治理结构,研发和开发大都市圈多元化机制政策工具等方面来构筑跨界治理体系,进而实现经济高质量一体化发展的目标.