Changes and Adjustments:The Rule of Law Response to Medical Institution Data Compliance

Medical institution data compliance is an exogenous product of the digital society,serving as a crucial means to maintain and balance the relationship between data protection and data sharing,as well as individual interests and public interests.The implementation of the Healthy China Initiative greatly benefits from its practical significance.In practice,data from medical institutions takes varied forms,including personally identifiable data collected before diagnosis and treatment,clinical medical data generated during diagnosis and treatment,medical data collected in public health management,and potential medical data generated in daily life.In the new journey of comprehensively promoting the Chinese path to modernization,it is necessary to clarify the shift from an individual-oriented to a societal-oriented value system,highlighting the reinforcing role of the trust concept.Guided by the principle of minimizing data utilization,the focus is on the new developments and changes in medical institution data in the postpandemic era.This involves a series of measures such as fulfilling the obligation of notification and consent,specifying the scope of data collection and usage,strengthening the standardized use of relevant technical measures,and establishing a sound legal responsibility system for data compliance.Through these measures,a flexible and efficient medical institution data compliance system can be constructed.

An Extensive Study and Review of Privacy Preservation Models for the Multi-Institutional Data

The deep learning models hold considerable potential for clinical applications, but there are many challenges to successfully training deep learning models. Large-scale data collection is required, which is frequently only possible through multi-institutional cooperation. Building large central repositories is one strategy for multi-institution studies. However, this is hampered by issues regarding data sharing, including patient privacy, data de-identification, regulation, intellectual property, and data storage. These difficulties have lessened the impracticality of central data storage. In this survey, we will look at 24 research publications that concentrate on machine learning approaches linked to privacy preservation techniques for multi-institutional data, highlighting the multiple shortcomings of the existing methodologies. Researching different approaches will be made simpler in this case based on a number of factors, such as performance measures, year of publication and journals, achievements of the strategies in numerical assessments, and other factors. A technique analysis that considers the benefits and drawbacks of the strategies is additionally provided. The article also looks at some potential areas for future research as well as the challenges associated with increasing the accuracy of privacy protection techniques. The comparative evaluation of the approaches offers a thorough justification for the research’s purpose.

网络文学排行榜:类型、功用及其批评形态建构

近年来,多种网络文学排行榜频繁发布,印证了网络文学的持续繁荣,也反映了社会关注力度的不断增强。网络文学排行榜经历了从“喜好榜”到“数据榜”、再到“数据榜”与“评选榜”并置的三个发展阶段。“数据榜”是引领消费的重要阅读指南,但其构建的“数据信仰”需要警惕。“评选榜”是网络文学批评的一种新形态,形成内含多种价值引导的“机构化批评”。当前的网络文学批评已经形成读者在线批评、媒体人批评、专家批评与“机构化批评”“四环联动”的批评机制。

新制度主义理论视域下激发我国政府数据开放驱动力的博弈分析

本研究旨在激发我国政府数据开放的驱动力,推动我国政府数据开放。以新制度主义理论为视角,分析了我国政府数据开放驱动力的构成,通过博弈分析方法研究影响我国政府数据开放驱动力发挥的原因,在此基础上,提出了激发我国政府数据开放驱动力的策略。我国政府数据开放的驱动力由外部驱动力和内部驱动力构成,应从完善法制建设、建立有效监管机制、满足数据用户需求、鼓励公众参与等途径激发驱动力。

社会学制度主义视角下地方政府创新行为的影响因素研究——一项对开放政府数据的实证研究

地方政府创新行为对全面深化改革和推进国家治理现代化发挥重要作用。结合地方政府创新实践,学界对地方政府创新行为影响因素进行了多角度的系统性研究,但仍缺乏从广义制度视角对地方政府创新行为的影响机制和机理的深入研究。本文基于社会学制度主义视角,从规制、规范、文化-认知三个维度深入分析影响地方政府创新行为的制度要素。以地方政府开放数据行为为实证对象的研究结果表明,制度环境形成同构有利于地方政府创新行为的开展,地方政府创新行为的调控可从合法性路径着手,并需要关注上级政府的行为示范、同侪压力以及公众参与对地方政府创新行为的促进作用。本文拓宽了社会学制度主义理论的应用场景,从广义制度层面揭示了我国地方政府创新行为的逻辑。

智能技术赋能下的大学治理形态变革

在人工智能、区块链、虚拟现实等新兴智能技术的影响下,大学治理需要在智能技术的全面渗透下实现个体、组织与制度的深度融合。从人类社会发展的历史看,技术形态的变迁最终决定着大学治理形态的变革;技术发展的“一切皆可数据化”趋势表明技术智能性与治理科学化之间存在一定的线性关系;数据治理、规则治理和程序智能将成为未来大学治理的主要形态。未来大学治理在个体层面,要通过提高个体的信息化素养和人机竞合能力,全面提升大学治理团队的专业化和职业化水平;在组织层面,要加大对院校数据的价值挖掘与整合力度,努力将各种数据用起来,充分发挥院校研究的价值,为大学决策提供最优方案;在制度层面,要注重大学制度的标准化建设和精细化发展,细化大学制度文本,变原则性规定为程序性规定,增强大学制度的可操作性和提升执行效果。

COLLECTING AND ANALYSING OUTCOMES DATA FROM ACUPUNCTURE TRAINING INSTITUTIONS: A COLLABORATIVE PROJECT

If clinical research is to be relevant to real-world decision making it requires interventions that reflect usual practice.Observational studies may provide the best approach to defining this.Siting studies in the student clinics of acupuncture teaching institutions(ATIs).has potential benefits for the institutions as well as for researchers.This is the first such multi-centre study accredited ATIs

GDPR时代数据保护的欧美标准与中国策略

欧盟《通用数据保护条例》(GDPR)实施后,各国数据保护制度逐步围绕“欧盟标准”“美国标准”展开研讨并形成集聚效应。关于“欧盟标准”“美国标准”的既有研究,多立足“合规需要”“现实影响”“比较视角”,较少采用理论框架系统评价两种数据保护制度的得失。本研究批判性地引入“制度化”四指标(“适应性”“复杂性”“自主性”“凝聚力”),评价以GDPR为代表的“欧盟标准”、以CCPA为代表的“美国标准”的制度化得失。同时,为构建“中国标准”提出创新策略:(1)增强“适应性”与“复杂性”,“中国标准”可介于“欧盟标准”和“美国标准”之间,融通“规制—权利”和“自律—责任”治理范式;(2)增强“自主性”与“凝聚力”,权威执法机关、数据跨境流动、分类分级制度将是制度建设的核心。