城市空间的改造、生产到正义侵蚀（巴黎1850—1890）

1850—1890年以奥斯曼为代表的统治者对巴黎城市空间进行功能性改造，塑造了巴黎新的景观社会并完成了空间生产化、秩序化、政治化的重构。资产阶级借助地租杠杆，利用空间政治工具性和政治功能性进行资本扩张的同时，也实现了阶层分化和新身份政治的形成。资本投机下的空间改造与生产使得巴黎无产阶级生存与发展的权益逐步被蚕食、侵害和剥夺，无产者对资产阶级的空间改造逐渐产生了由认同—消解—反抗的转向，空间正义意识开始觉醒。通过对城市空间规划改造中的阶级立场分析，论证空间正义与城市发展、阶层融合、社会排斥之间的联系机理，阐明资本主义空间规划与空间生产的固有缺陷，对当代城市的空间规划、贫困问题、社会排斥、城市包容性发展、环境更新与治理等现实问题提供新的视角启发与理路审视。     

论"通知—删除"规则的性质——以平台自治为视角

"通知—删除"规则的法律条文并没有赋予平台自治的空间,但是平台自治的需求已经"凸显".免责条款理论表面上能保障平台自治,但是并不符合我国的实际.归责条款理论是我国的通说,其扼杀了平台自治的空间,司法实践对此虽有调和,但是难以济事.我国的"通知—删除"规则系特定的历史背景下的产物,其在性质上仅仅是行为标准.在侵权行为的认定上,违反"通知—删除"规则的情形并非侵权的充分条件.事实上,这一行为标准的违反在侵权法上的意义仅仅作为主观过错的证据,电商平台可以反证其不具有过错.司法实践中亦有区别对待"通知—删除"规则的违反和侵权之认定的做法.明晰此点方可保障平台自治,同时亦实现电商平台对用户监管之目的.     

科技创新、产业复杂度与经济增长

科技创新能够通过产业复杂度的变化对经济增长产生影响.以1995—2019年世界银行和哈佛大学Atlas数据库的科技创新为研究样本,运用中介效应检验方法,考察科技创新如何通过纺织类、农业类、钻石类、矿产类、金属类、化工类、汽车类、设备类和电子类的产业复杂度变化来影响国民生产总值,从而揭示了科技创新如何通过产业复杂度的变化影响经济增长的机理.研究结果表明:从总体上看,科技创新影响经济增长的过程中,产业复杂度的中介效应量为90.83％,具有显著性,其中农业类、钻石类以及矿产类相关系数为负,其他类别相关系数为正,电子类作用程度最高.区分经济体类型的研究结果显示:产业复杂度的中介效应存在异质性,发达经济体、亚洲经济体、技术密集型经济体存在相对优势,而且科技创新促进经济增长开启了"机会窗口期",后发经济体可以实现"弯道超车".这一研究结论有助于丰富科技创新领域的相关成果,能够为引导产业转型升级方向、提高国家经济增长能力提供理论依据和经验借鉴.     

城市老年人对居家养老服务提供主体的选择及影响因素——基于福利多元主义视角的研究

居家养老是我国社会化养老服务的基础,诞生于西方发达国家的福利多元主义为我国国家主导型社会福利政策和居家养老服务的发展提供了理论资源。当前我国城市地区的居家养老服务主要依靠政府推动,市场化机制开始建立,老年群体对政府、社区依赖较高,对市场化服务供给主体的认可度仍有较大提升空间。加快发展居家养老服务,满足不同社会人口和经济特征老年人的多样化需求是一项社会系统工程。在创建多元化服务格局的过程中,需要政府、企业、社区、社会组织、志愿者、家庭和个人等各方参与主体明确权责,分工协作,扩大有效需求,统筹地区协调发展,凝聚推动供需两旺良性发展的合力。     

Partial Identification of Economic Mobility: With an Application to the United States

Abstract

The economic mobility of individuals and households is of fundamental interest. While many measures of economic mobility exist, reliance on transition matrices remains pervasive due to simplicity and ease of interpretation. However, estimation of transition matrices is complicated by the well-acknowledged problem of measurement error in self-reported and even administrative data. Existing methods of addressing measurement error are complex, rely on numerous strong assumptions, and often require data from more than two periods. In this article, we investigate what can be learned about economic mobility as measured via transition matrices while formally accounting for measurement error in a reasonably transparent manner. To do so, we develop a nonparametric partial identification approach to bound transition probabilities under various assumptions on the measurement error and mobility processes. This approach is applied to panel data from the United States to explore short-run mobility before and after the Great Recession.     

Efficient Estimation in Heteroscedastic Partially Linear Varying Coefficient Models

This article considers statistical inference for the heteroscedastic partially linear varying coefficient models. We construct an efficient estimator for the parametric component by applying the weighted profile least-squares approach, and show that it is semiparametrically efficient in the sense that the inverse of the asymptotic variance of the estimator reaches the semiparametric efficiency bound. Simulation studies are conducted to illustrate the performance of the proposed method.     

城市年轻母亲育儿感受与育儿支援——基于北京与南京4所幼儿园的调查研究

本研究运用调查分析的方法了解大城市年轻母亲在育儿过程中的感受。研究发现,夫妻共同分担家庭育儿责任的观念深入人心,母亲在孩子成长中的重要性也得到肯定。养育孩子使年轻的母亲既充满了快乐和幸福,也伴随着各种不安和焦虑;她们普遍感到育儿支援存在缺陷,以至于难以从容面对育儿过程,希望能够获得比较充裕的社会资源,有一个良好的社会支持网络,帮助她们顺利完成育儿过程。为此建议,政府应制定相应的政策法规,提供一定的资金支持,加强对处于育儿期家庭的人文关怀;进一步强化男女平等意识,促进父亲更多地参与日常育儿活动;建立网上支援系统;改善城市规划建设,为育儿提供更好的空间环境。     

Linear scalar-on-surface random effects regression models

Many research fields increasingly involve analyzing data of a complex structure. Models investigating the dependence of a response on a predictor have moved beyond the ordinary scalar-on-vector regression. We propose a regression model for a scalar response and a surface (or a bivariate function) predictor. The predictor has a random component and the regression model falls in the framework of linear random effects models. We estimate the model parameters via maximizing the log-likelihood with the ECME (Expectation/Conditional Maximization Either) algorithm. We use the approach to analyze a data set where the response is the neuroticism score and the predictor is the resting-state brain function image. In the simulations we tried, the approach has better performance than two other approaches, a functional principal component regression approach and a smooth scalar-on-image regression approach.     

How leader role identity influences the process of leader emergence: A social network analysis

Contemporary theories on leadership development emphasize the importance of having a leader identity in building leadership skills and functioning effectively as leaders. We build on this approach by unpacking the role leader identity plays in the leader emergence process. Taking the perspective that leadership is a dynamic social process between group members, we propose a social network-based process model whereby leader role identity predicts network centrality (i.e., betweenness and indegree), which then contributes to leader emergence. We test our model using a sample of 88 cadets participating in a leadership development training course. In support of our model, cadets who possess a stronger leader role identity at the beginning of the course were more likely to emerge as leaders. However this relationship was only mediated by one form of network centrality, indegree centrality, reflecting one's ability to build relationships within one's group. Implications for research and practice are discussed.