对垃圾邮件侵犯网络隐私权的法律规制

垃圾邮件更大程度上侵害的是收件人的隐私权,或者说是安宁享受生活而不受不正当的侵扰的权利。很多国家从保障互联网使用者的隐私权为出发点制定了反垃圾邮件立法。我国法律对隐私权的保护没有规定,反垃圾邮件立法也相对滞后,使垃圾邮件有泛滥趋势。对滥发垃圾邮件的行为加以制止,对网络个人信息资料使用行为进行规范,同时也使网络个人资料的控制与利用制度进一步得到完善,是我国立法面临的一个重要问题。     

试论我国证券监管的模式

证券监管是金融监管的重要组成部分,金融监管理论同样适用于证券 监管。我国的证券监管工作有待进一步研究和完善,如证监会的法律责任不明确等。 目前,西方国家证券监管有不同模式,我国应借鉴有益经验,在加强证券监管中,注意 从几个方面着手：正确选择制度设计的价值取向;创造良好的制度环境;完善法制建 设;优化监管体制设计。     

中国农民法律意识现状探讨

农民法律意识的内部架构是,法律意识淡漠与对传统伦理和乡土规范的青睐相伴。其成因是：简单经济关系使其亲近法律缺少利益的驱动;农村家庭的生产职能滋养了具有生产组织文化特点的儒家伦理;人治传统下法律的作用使其缺少对法律的利益感受。觉醒农民法律意识有益于：构建市场经济运动之基础和市民社会之人格——心理基础;塑造崇尚权利的现代法治和民主政治运行之逻辑习惯。     

论卧底警察的保护与规制

随着有组织犯罪的日益猖獗,公安机关运用卧底警察进行侦查破案的策略日益受到人们的关注。然而由于我国相较于其他世界发达国家在这方面的立法及制度建设还存在极大的滞后性,因此,理论界学者有必要对卧底警察这一被广泛运用的现象给以正确评价、规制和保护,以满足当今刑事侦查工作的切实需要。     

论行政规定在行政诉讼中的效力

在现行法律体制下,行政规定不属于法律渊源,不是行政诉讼中法院必须适用的法律依据。但行政规定是行政机关作出行政行为的依据,在现实社会中具有重要的规范功能。在行政诉讼中,法院对行政规定既不能完全抛开,又不能完全信任。为了回应社会现实,应当在形式法治的框架内,融入部分实质法治的要素,附条件地承认行政规定的效力,并由法院依照这些条件和规则予以审查。     

房地产价格行政规制

近几年我国房地产价格持续暴涨,严重影响到千家万户的正常生活.为了维护家庭、社会的和谐稳定以及房地产市场的健康发展,多角度分析我国房地产价格持续暴涨的原因,探索近期及中长期不同对策,对于制定当下规范化的有效规制措施、促进我国房地产价格稳定、构建和谐社会乃至未来土地政策、法律体系的建立都具有重要意义.     

外国人在华非法就业管理制度探析

根据不同的移民管理制度,国内学者将外国人就业区分为职业移民与国际劳工。职业移民多为移民国家所采用。作为非移民国家,我国现行外国人就业管理制度体系并不完善,仅仅对国际劳工中具有专业技术外国人员的劳动就业进行规范,即便中国式＂绿卡＂制度也采取有条件地实行从国际劳工向永久居留资格转变的方式。外国人就业管理制度理应与移民取向相并行,但现行管理制度并不适合我国发展现状,构建新型管理制度势在必行。     

反垄断法的挑战——对反垄断法的整体主义解释

反垄断法是新时代、新观念的产物。它对当前处于主流地位的部门法提出了一系列的挑战,主要体现为四方面的转向:第一,从传统法注重对法律关系两头的人的保护转向对主体间关系的保护;第二,从保护个体利益转向保护社会整体利益;第三,从传统法对行为违法性判定的条件取向转向结果取向;第四,从传统法的责任导向转向规制导向,即从重在禁于已然之后转向重在禁于未然之前。     

Are ‘pseudonymised’ data always personal data? Implications of the GDPR for administrative data research in the UK

There has naturally been a good deal of discussion of the forthcoming General Data Protection Regulation. One issue of interest to all data controllers, and of particular concern for researchers, is whether the GDPR expands the scope of personal data through the introduction of the term ‘pseudonymisation’ in Article 4(5). If all data which have been ‘pseudonymised’ in the conventional sense of the word (e.g. key-coded) are to be treated as personal data, this would have serious implications for research. Administrative data research, which is carried out on data routinely collected and held by public authorities, would be particularly affected as the sharing of de-identified data could constitute the unconsented disclosure of identifiable information.Instead, however, we argue that the definition of pseudonymisation in Article 4(5) GDPR will not expand the category of personal data, and that there is no intention that it should do so. The definition of pseudonymisation under the GDPR is not intended to determine whether data are personal data; indeed it is clear that all data falling within this definition are personal data. Rather, it is Recital 26 and its requirement of a ‘means reasonably likely to be used’ which remains the relevant test as to whether data are personal. This leaves open the possibility that data which have been ‘pseudonymised’ in the conventional sense of key-coding can still be rendered anonymous. There may also be circumstances in which data which have undergone pseudonymisation within one organisation could be anonymous for a third party. We explain how, with reference to the data environment factors as set out in the UK Anonymisation Network's Anonymisation Decision-Making Framework.     

Clarity,surprises, and further questions in the Article 29 Working Party draft guidance on automated decision-making and profiling

The Article 29 Data Protection Working Party's recent draft guidance on automated decision-making and profiling seeks to clarify European data protection (DP) law's little-used right to prevent automated decision-making, as well as the provisions around profiling more broadly, in the run-up to the General Data Protection Regulation. In this paper, we analyse these new guidelines in the context of recent scholarly debates and technological concerns. They foray into the less-trodden areas of bias and non-discrimination, the significance of advertising, the nature of “solely” automated decisions, impacts upon groups and the inference of special categories of data—at times, appearing more to be making or extending rules than to be interpreting them. At the same time, they provide only partial clarity – and perhaps even some extra confusion – around both the much discussed “right to an explanation” and the apparent prohibition on significant automated decisions concerning children. The Working Party appears to feel less mandated to adjudicate in these conflicts between the recitals and the enacting articles than to explore altogether new avenues. Nevertheless, the directions they choose to explore are particularly important ones for the future governance of machine learning and artificial intelligence in Europe and beyond.