针对生物识别信息的刑法保护:现实境遇与完善路径——以四川“人脸识别案”为切入点

当前生物识别信息在我国社会中的运用呈现逐年递增的趋势.生物识别信息具备本体特殊性和社会特殊性,这决定了其具备与普通公民个人信息不同的重要性,应受到刑法的特殊保护,但我国既定刑事立法对生物识别信息并未进行任何形式的特殊保护.可运用实质解释的方法,在不违反罪刑法定原则的前提下,充分利用两高《解释》第5条中第1款第10项和第2款第4项这两个兜底条款,将"侵犯生物识别信息5条及以上"认定为"情节严重",将"侵犯生物识别信息50条及以上"认定为"情节特别严重",由此降低针对生物识别信息原本的入罪和法定刑升格的数量,最终实现对生物识别信息的特殊刑法保护.     

局部平稳部分线性面板数据模型的统计推断

部分线性模型是一类非常重要的半参数回归模型,由于它既含有参数部分又含有非参数部分,与常规的线性模型相比具有更强的适应性和解释能力。文章研究带有局部平稳协变量的固定效应部分线性面板数据模型的统计推断。首先提出一个两阶段估计方法得到模型中未知参数和非参数函数的估计,并证明估计量的渐近性质,然后运用不变原理构造出非参数函数的一致置信带,最后通过数值模拟研究和实例分析验证了该方法的有效性。     

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.     

Tests for homogeneity of risk differences in stratified design with correlated bilateral data

ABSTRACT

Correlated bilateral data arise from stratified studies involving paired body organs in a subject. When it is desirable to conduct inference on the scale of risk difference, one needs first to assess the assumption of homogeneity in risk differences across strata. For testing homogeneity of risk differences, we herein propose eight methods derived respectively from weighted-least-squares (WLS), the Mantel-Haenszel (MH) estimator, the WLS method in combination with inverse hyperbolic tangent transformation, and the test statistics based on their log-transformation, the modified Score test statistic and Likelihood ratio test statistic. Simulation results showed that four of the tests perform well in general, with the tests based on the WLS method and inverse hyperbolic tangent transformation always performing satisfactorily even under small sample size designs. The methods are illustrated with a dataset.     

Challenges of operationalizing trauma‐informed practice in child protection services in New Zealand

New Zealand is undergoing major change in service delivery to children and families. A new Ministry for Children Oranga Tamariki has been established to oversee 5 work streams, one of which provides intensive intervention with families requiring a statutory response to child protection concerns. The government minister responsible promised that the service would be child‐centred and trauma‐informed. To date, these terms remain undefined, and there is no shared understanding of their meaning. Practice frameworks to support the work of the new ministry are still being developed, creating something of a vacuum in the meantime. The focus of this paper is the challenge of implementing trauma‐informed practice in the child protection service provided by the Intensive Intervention work stream. Limited research or commentary on trauma‐informed practice in this context currently exists. Drawing on the relevant available literature, the concept and its application in child protection social work is explored. An ecological framework is used to discuss the changes needed to achieve this. Particular attention is paid to the impact of historical trauma for indigenous people due to New Zealand's colonial history and their over‐representation in care and protection services.     

Bayesian inference for stable Lévy–driven stochastic differential equations with high‐frequency data

In this paper, we consider parametric Bayesian inference for stochastic differential equations driven by a pure‐jump stable Lévy process, which is observed at high frequency. In most cases of practical interest, the likelihood function is not available; hence, we use a quasi‐likelihood and place an associated prior on the unknown parameters. It is shown under regularity conditions that there is a Bernstein–von Mises theorem associated to the posterior. We then develop a Markov chain Monte Carlo algorithm for Bayesian inference, and assisted with theoretical results, we show how to scale Metropolis–Hastings proposals when the frequency of the data grows, in order to prevent the acceptance ratio from going to zero in the large data limit. Our algorithm is presented on numerical examples that help verify our theoretical findings.     

大数据时代项目评审中社会伦理问题的对抗性设计

通过对抗性设计方法解决项目评审中的社会伦理问题，为专家、申请者、大众提供争论和表达异议的民主环境。项目自动评价平台完成民主环境的构建，呈现专家、申请者、平台的争胜性关系，揭示霸权，旨在重塑自由、平等、公平、正义、特权等的项目评审中的社会伦理。     

我国中小学校园欺凌问题研究及薄弱环节——基于CNKI文献关键词的共词分析

随着一系列恶性事件被媒体曝光，社会各界普遍关注和担忧校园欺凌问题，如何解决这一问题，已成为社会焦点。通过共词分析法对我国中小学校园欺凌问题研究现状进行考察发现，其研究主题主要包括六大类：校园欺凌行为特征研究、校园欺凌与学校管理的关系研究、校园欺凌与人际交往的关系研究、校园欺凌的成因与对策研究、校园欺凌的预防与治理研究、校园欺凌的社会问题研究，而研究的薄弱环节则主要包括品格教育研究、学生自我保护研究以及网络欺凌问题研究。因此，校园欺凌问题研究亟待进一步深化，研究视角也需进一步拓展。首先，除欺凌者、被欺凌者之外，旁观者也应纳入研究范畴，要将欺凌者和被欺凌者实施隔离，对受欺凌者要及时给予心理疏导，引导旁观者积极主动地帮助被欺凌者；其次，建议尽快出台相关的法律法规，为学校、教师及相关部门有效处理、解决校园欺凌问题提供法律支持及保障；最后，将综合预防与治理相结合，建立由学校、教师、学生组成的反欺凌共同体。     

Probabilistic frontier regression models for binary type output data

This paper proposes a probabilistic frontier regression model for binary type output data in a production process setup. We consider one of the two categories of outputs as ‘selected’ category and the reduction in probability of falling in this category is attributed to the reduction in technical efficiency (TE) of the decision-making unit. An efficiency measure is proposed to determine the deviations of individual units from the probabilistic frontier. Simulation results show that the average estimated TE component is close to its true value. An application of the proposed method to the data related to the Indian public sector banking system is provided where the output variable is the indicator of level of non-performing assets. Individual TE is obtained for each of the banks under consideration. Among the public sector banks, Andhra bank is found to be the most efficient, whereas the United Bank of India is the least.     

全媒体时代主流媒体的数据化生存与发展

基于互联网连接的媒体平台，正在成为各类原生数据的源发地和汇聚中心，对大数据进行整合及应用的能力，将成为未来媒体平台运营的核心能力。建构在互联网平台之上的主流媒体必然要经历从信息总汇向数据总汇的转变，在这一过程中，媒体的业态、社会功能都将发生重大变化。伴随全媒体时代信息技术的快速发展，新闻传播呈现出新的特点和规律：传播主体大众化；传播容量海量化；传播方式交互化；传播手段多维化；传播时效全时化。在这样的背景下，主流媒体应不断进行数据化的探索和创新，基于5G网络，通过大数据技术运用，强化数据库建设，以此为基础，运用基于大数据的人工智能技术改变内容生产和分发方式，并以之作为内容监管的有力武器。未来基于大数据分析的综合业务推动自身产业结构优化。