"数据库专有权"的创设

数据库是用系统的、有顺序的方式编排的独立的作品、数据或其他材料的集合,具有信息性、系统性和可访问性等特征;传统版权保护模式是国际社会对数据库的主要保护模式,而新型版权(邻接权)保护模式、欧盟特殊权利保护模式以及以反不正当竞争法为主要保护手段的非权利保护模式是对传统版权模式的修正,它们各具缺陷;创设"数据库专有权"是数据库保护模式的理性选择.     

互联网信息产权交易的规范形态

根据互联网发展的阶段性特征,可以归纳出信息产权民事法律保护的三个理想型规范形态:第一是互联网个人信息安全的产权保护模式,其规范形态是底层数据安全与隐私权为主的事后救济。第二是互联网平台信息产权交易法律保护,以知识产权、反不正当竞争法、消费者权益保护法为主的事前授权规范。第三是互联网+信息产权交易价值共享法律保护,形成共享激励模式,以反垄断法为主的事中规制规范。数字经济不同于市场经济的市场分配方式,需要以信息产品定价机制来分配信息产权,形成公法嵌入私法的法律规范模式。     

《民法总则》胎儿利益保护条款的法律适用

为明确《中华人民共和国民法总则》创设的胎儿利益保护条款的法律适用,通过比较医学上和法律上胎儿概念的不同,探讨胎儿的民事权利能力的起止期间、附加条件和权利范围。提出胎儿的民事权利能力始于受孕之日、终于出生之日;胎儿娩出时为死体的,自始不具有民事权利能力;胎儿娩出时为活体的,胎儿具有遗产继承、接受赠与、损害赔偿等权利。胎儿利益保护条款实现了我国自然人权益保障上的突破,但还需要有权机关对胎儿利益保护条款作出明确的解释。     

关于企业集团立法的几点思考

企业集团在我国经济发展中已经具有举足轻重的地位,在企业经营方式上,也逐渐取代单一企业成为企业发展的主流。虽然我国《公司法》、《反不正当竞争法》等法的出台为规范企业行为提供了重要的法律保障,但是,这些法律主要是以单一企业为规范对象,对于企业集团的运作并...     

对台湾地区“病人自主权利法”的评述及启示

台湾地区"病人自主权利法"不仅保障临终病人的善终权,同时也对病人的其他权利进行完整规制,以确保病人在诊疗过程中的尊严与地位。以其立法背景为切入点,从规制病人权利、完善权利保障措施、节约医疗资源三个角度揭示其立法必要性,探讨病人自主权与医生决定权的共融、自主善终与安乐死的差异等相关问题。提出大陆地区应在法律引导下明确病人权益,多部门协作推动建立生前预嘱制度与临终关怀体系,以达到缓解医患矛盾与保障病人权利的目的。     

我国体育赛事转播权的保护模式及其完善路径

当前体育赛事转播权的法律性质仍存有较大争议。虽然新修订的《体育法》第52条明确了体育赛事活动的保护规则，但仍未能解决体育赛事转播权的性质界定问题。在体育赛事转播权的理论观点尚不能做到逻辑自洽之际，将体育赛事转播权视为一种民事法益，并为其提供有限保护，既能有效协调体育赛事活动中各相关主体的利益，也能维持现有民事权利体系的完整性。体育赛事转播权的法益保护模式构建起了体育赛事转播权的动态利益平衡机制，并为体育赛事转播权的权利法定化保留了制度空间。     

虚拟财产的刑法保护对策研究

近年来,有关虚拟财产的法律纠纷增多,刑法对此保护缺位凸显,表现为保护的内容非常有限,依传统规制思路下的网络工具犯的刑法适用来保护虚拟财产还存在理论困境,若只关注网络正义价值的实现,而忽略对网络秩序价值的维护,刑法将不能起到有效的保护效果。基于此提出以下改进措施,首先,需要将"信息网络"作为犯罪对象的一种新类型,从而将虚拟财产涵盖其中,以规避对"物"的争议;其次,有必要对现行《刑法》第285条和第286条进行重构,以维护虚拟财产承载着的网络虚拟秩序这一特殊法益,避免过多地陷入网络工具犯的刑法适用。     

专利聚合的法律规制研究

专利聚合是专利制度由保护权利到限制竞争的一种异化,也是专利权由合法行使向权利滥用演变的商业模式,但是这种模式介于专利权的合法行使与限制竞争的垄断行为之间,逐渐成为一般性专利权滥用的新类型,其后果不仅会增加生产成本,使专利技术实施偏离专利制度的宗旨,甚至阻碍技术市场的自由竞争和良性发展。因此需要对其是否需要法律规制进行研究。本文认为,在专利法中确立禁止一般性专利权滥用的规则是目前对专利聚合法律规制的最佳路径。     

病人的权力与维护

1医疗侵权行为及其产生的原因 医疗侵权行为是指医务人员在治疗、护理过程中侵害了患者的非合同权利或受法律所保护的利益,它不仅包括医疗事故,还包括因诊疗、护理过失使患者病情加重,受到死亡、残废、功能障碍以外的一般损伤及痛苦的医疗差错,以及既不属于医疗事故和医疗差错的一般侵权行为.医疗侵权的范围是相当广泛的.只要是医务人员侵犯了患者受法律保护的权利或利益,造成损害后果的,在具备主观过错和因果关系时,便可能构成医疗侵权.     

我国宗教财产保护的问题及对策北大核心CSSCISSCI

加强宗教财产的法律保护是推进宗教事务法制化的关键环节,亟需认真研究和落实。由于宗教财产权的归属一直没有得到法律上的明确,实践中的宗教财产权属关系不明导致的社会乱象比比皆是,宗教团体及相关利益主体之间的宗教财产纠纷频频发生,商业化、市场化浪潮冲击下的寺庙宫观成为公众舆论关注的焦点。这些现象严重扰乱了正常的宗教活动秩序,损害了宗教界的权益与形象,也对目前实行的以政策调整为主、法律调整为辅的宗教财产保护体制提出挑战。     

推进开放政府数据:提升政府部门大数据能力

开放政府数据能够助力政府实现公共治理变革。近年来,我国各级政府均在进行开放政府数据工作,但目前存在开放数据量少、质量不高、再利用性低等问题,这些问题与缺乏政府部门大数据能力有关,因此,探索如何提升政府部门大数据能力极为必要。通过分析我国目前开放政府数据的现状与美国的案例,本文认为,可以通过探索首席信息官制度、加强数据脱敏等工作、推动法制建设等方式来加强政府部门大数据能力,从而将我国开放政府数据工作落于实处,充分发挥政府大数据的巨大价值。     

Data Labours: How the Sequence Databases GenBank and EMBL-Bank Make Data

What actually happens inside genetic databases, how do they work upon data and who does this work? While they have become central tools for doing science, not much is known about the work that goes on inside these vital infrastructures. Ethnographic explorations of two of the world’s largest nucleotide sequence databases, GenBank and the European Molecular Biology Laboratory’s EMBL-Bank, reveal manifold goings-on. Like most infrastructural work, it is modest and invisible routines that build and maintain the vast interconnected suite of bioinformational resources. Data curators construct organisms out of sulphuric sludge, dataflow engineers as self-styled “genetic information plumbers” keep the data deluge flowing, and a data submissions support assistant manages to make room for care amidst this deluge. Taken together, these data labours render tangible the modest and processual aspects of data infrastructure while also revealing the databases to be situated and lively spaces of convergence. Inventively analysing data labours paves surprising ways for encountering and making sense of databases, data and the work they do. Here, practices of natural history, like specimen-making and curation, are continued by other means while the assembly of sludge sheds light on the absences and deletions which mystify infrastructural maintenance work.     

Big Data,Big Waste? A Reflection on the Environmental Sustainability of Big Data Initiatives

Science and Engineering Ethics - This paper addresses a problem that has so far been neglected by scholars investigating the ethics of Big Data and policy makers: that is the ethical implications...     

On the Measurement of Stability in Over-Time Data

ABSTRACT In this article, autoregressive models and growth curve models are compared Autoregressive models are useful because they allow for random change, permit scores to increase or decrease, and do not require strong assumptions about the level of measurement Three previously presented designs for estimating stability are described (a) time-series, (b) simplex, and (c) two-wave, one-factor methods A two-wave, multiple-factor model also is presented, in which the variables are assumed to be caused by a set of latent variables The factor structure does not change over time and so the synchronous relationships are temporally invariant The factors do not cause each other and have the same stability The parameters of the model are the factor loading structure, each variable's reliability, and the stability of the factors We apply the model to two data sets For eight cognitive skill variables measured at four times, the 2-year stability is estimated to be 92 and the 6-year stability is 83 For nine personality variables, the 3-year stability is 68 We speculate that for many variables there are two components one component that changes very slowly (the trait component) and another that changes very rapidly (the state component), thus each variable is a mixture of trait and state Circumstantial evidence supporting this view is presented     

Data analysis and the connectivity of random graphs

This paper presents empirical information on the adequacy of an asymptotic approximation developed by Erdös and Rényi dealing with the minimum number of lines needed to connect a random graph. It is shown that the approximation is poor for several data analysis applications of the result previously published in the behavioral sciences.     

Models of Data: A Theory of How People Evaluate Data

This article reports the results of a study investigating how undergraduates evaluate realistic scientific data in the domains of geology and paleontology. The results are used to test several predictions of a theory of data evaluation, which we call models-of-data theory. Models-of-data theory assumes that when evaluating data, the individual constructs a particular kind of cognitive model that integrates many features of the data with a theoretical interpretation of the data. The individual evaluates the model by attempting to generate alternative causal explanations for the events in the model. We contrast models-of-data theory with other proposals for how data are cognitively represented and show that models-of-data theory gives a good account of the pattern of written evaluations of data produced by the undergraduates in the study. We discuss theoretical and instructional implications of the theory.     

Data on the role of the frontal cortex in vegetative behavior

A homeostatic conditional reflex (CR) was elaborated to the effect of repeated inhalations in rats of a gas mixture containing 8 per cent oxygen. The effect of the conditional response was opposite to that of the unconditional one. After ablation of the frontal cortex, the conditional reaction disappeared. The repeated administration of 40 mg/kg of histamine resulted in a tolerance to the temperature lowering effect of histamine similar to the habituation. An injection of distilled water brought about dishabituation. Tolerance was not influenced by the ablation of the frontal cortex, but the dishabituating effect of distilled water was absent.     

Your Data are (Not) My Data: The Role of Social Value Orientation in Sharing Data About Others

The personal data consumers share with companies on a daily basis often also involves other people. However, prior research has focused almost exclusively on how consumers make decisions about their own data. In this research, we explore how consumers’ social value orientation impacts their decisions regarding data about others. In contrast to the notion of proselfs as “selfish” decision-makers, across four studies we find that proselfs are less likely than prosocials to share data about others with third parties. We show that this effect arises because proselfs feel less ownership over data they hold about others than prosocials, which in turn reduces their willingness to share it. Overall, this work contributes to literature on social value orientation as well as privacy decision-making and helps marketers and policy makers in designing interdependent privacy choice contexts.