论党的群众工作优良传统与社会工作创新

群众工作是我党的优良传统和政治优势,社会工作是解决社会问题的重要手段,在社会主义全面深化改革阶段,面临新的社会形势,群众工作与社会工作迫切需要创新。将党的群众工作优良传统与社会工作创新结合起来探讨,一方面有利于群众工作的创新;另一方面有利于社会工作的本土化发展。     

国有企业CEO注意力对产品创新影响的研究

在探讨了CEO注意力、产品创新表现与企业绩效之间的关系的基础上,构建了有关理论模型,并通过问卷收集的方法对国有企业CEO进行了调研。研究结果表明,国有企业CEO对于外部的注意力普遍高于其对内部的注意力;外部注意力对于产品创新的技术表现和市场表现均有积极影响,内部注意力仅与产品创新的技术表现正向相关;产品创新的技术表现对于企业的财务绩效和非财务绩效均有积极影响,仅市场表现对企业非财务绩效有积极影响。     

Social innovation and ICT in social services: European experiences compared

Innovation in social services and social policies in the European welfare systems is an evolving phenomenon stimulated by socio-demographic, cultural and economic changes. Many social service innovations are linked to disruptive technologies, especially the introduction of information and communication technology (ICT). To discuss the effects of disruptive technologies on health and social services, this article first proposes a framework consistent with the social innovation paradigm. Secondly, based on case-studies, it investigates different models of social and health service innovation driven by technology. The article shows advantages and disadvantages of service innovation driven by technology, and offers some final remarks about future challenges for ICT in health and social services. More evidences of effectiveness and efficiency are necessary to promote public and private investment to implement solutions on a wider scale. However, the impacts of technology-based solutions cannot be measured only in terms of economic aspects but also taking into account whether new technologies really provide the opportunity for citizens to have a better life and advocacy for their rights.     

The role of events in ICT adoption: same-sex marriage and Twitter

ICT adoption is predominantly considered as a process conditioned by social structures, social situations of adopters, and attributes and features of technologies. What is often overlooked are the cultural forces that shape adoption experiences and processes. This paper focuses on events and event narratives as vehicles through which the efficacy of culture unfolds in technological change processes. Cultural sociology has shown how influential events can be for forming public opinions and facilitating collective action. This article considers the power of one event on a much smaller scale: the passage of same-sex marriage (SSM) law in New York in June 2011 was not only significant for marriage equality in the US but also for the operating logic of the news ecosystem in which the political decision was made ? the state house in Albany. For the journalists who covered this event on the ground, the SSM decision was the catalyst to fully embrace Twitter. Years later, the event still served as an exemplar for the potentials of Twitter and as a basis of legitimacy of associated tweeting practices reporters incorporated. This contribution is based on ethnographic research at the state house in Albany, analysis of tweets and legacy news coverage published during that period, and in-depth interviews with reporters.     

高端装备制造业知识网络有效性影响因素分析

分析影响高端装备制造业知识网络有效性的五个因素,构建知识网络有效性模型并进行仿真分析,得出结论:企业为提高知识吸收能力和知识释放意愿所做投入在一定范围内可以提升知识网络有效性,投入超过一定值后,这种提升作用不再明显;企业较高的知识水平、企业间良好的合作关系与适当的知识势差可以提高知识网络有效性,并根据仿真结果提出相关建议。     

21世纪以来我国教师教育研究图景与发展路向——基于2000-2018年CSSCI来源期刊的知识图谱分析

教师教育是教育事业的重中之重。通过中国知网检索21世纪以来CSSCI来源期刊中的相关文献，以其中2 171篇有关教师教育研究的论文为样本，运用文献计量分析可视化软件Cite Space对文献数量、作者贡献、研究热点、研究层次以及论文被引情况等进行详细统计与梳理，旨在通过知识图谱的方法客观地揭示21世纪以来我国教师教育研究图景，并对教师教育研究发展路向进行全景式分析与展望。就文献数量而言，教师教育研究曲折发展，整体呈上升趋势；就作者贡献而言，尚未形成教师教育研究的核心作者群体，作者大多为高等院校的专家学者，而一线教师、教研员较少；就研究热点而言，主要呈现出有关教师教育的理论研究、改革研究和国别研究三大研究主题；就研究层次而言，主要集中于基础研究。基于此，应进一步加强教师教育研究队伍建设，尽快形成教师教育研究核心作者群体；鼓励多种力量参与研究，进一步丰富研究层次；拓展研究领域，探索教师教育研究多元化发展的新路向。无论是党的十九大报告，还是《教师教育振兴行动计划（2018-2022年）》，都对新时代教师教育提出了更高的要求。师德教育如何推进，教师素质如何提高，教师待遇如何改善，教师教育模式如何创新，教师管理制度改革如何深化，教师教育研究共同体如何构建，这一系列问题需要教师教育研究者深入探索，在习近平新时代中国特色社会主义思想和全国教育大会精神的指引下，为新时代高素质、专业化、创新型教师队伍的建设与发展建言献策。     

Financing Innovation Development in the Context of Foreign Experience and Domestic Practice

The importance of innovation development is determined by the strategic role that true innovations play in the development of the state and the formation of a healthy, competitive economy. The organization of massive industrial production—which applies advanced technological achievements and science-intensive knowledge to form an infrastructure for innovation—should be a key component of the government’s strategic policy to develop the national economy. In Russia, the infrastructure for innovation is less developed than other industrialized countries. This article considers the consequences of this underdevelopment, and proposes several ways of financing basic and applied research on the basis of foreign precedent and domestic practice.     

生产性服务业对出口贸易的影响研究

生产性服务业将人力资本和知识资本导入生产过程促进了制造业升级,其发展程度代表着一个国家或地区的现代化程度。充分有效利用服务业资源已成为工业企业提高竞争力进而扩大出口贸易的必然选择。从专业化分工、技术创新等方面探讨生产性服务业对出口贸易的影响机理,结合辽宁省生产性服务业发展状况建立面板数据模型,对其是否影响辽宁出口贸易进行实证分析,结果证实辽宁生产性服务业发展促进了出口贸易发展,交通运输、仓储及邮政和商务服务业对辽宁出口贸易的影响较为明显。据此提出发展生产性服务业以促进辽宁贸易的建议。     

高校党外知识分子思想政治教育工作的传承与创新

高校是党外知识分子的集中之地。在新的社会条件下，做好高校党外知识分子思想政治教育工作，是高等教育全面、协调、可持续发展的重要保障。必须在坚持一致性和多样性统一的前提下，找到最大公约数，画出最大同心圆，为国家实施科教兴国、人才强国和创新驱动发展战略，为高校的改革与发展凝聚人心、汇聚力量。     

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.