New calibration estimator based on two auxiliary variables in stratified sampling

In recent years, calibration estimation has become an important field of research in survey sampling. This paper proposes a new calibration estimator for the population mean in the presence of two auxiliary variables in stratified sampling. The theory of new calibration estimator is given and optimum calibration weights are derived. A simulation study is carried out to performance of the proposed calibration estimator over other existing calibration estimators. The results reveal that the proposed calibration estimators are more efficient than other existing calibration estimators in stratified sampling.     

网络视频实时在线评论用户认可度的影响因素

目前，网络视频实时在线评论激增带来的信息爆炸，使实时在线评论信息管理成为重要议题。以往对实时在线评论的研究多集中于个人行为结果方面，而缺乏对实时在线评论信息管理问题的关注；同时，现有视频网站对实时在线评论信息的管理也存在诸多局限。以爱奇艺视频网站热度榜中的电影为样本，基于信息质量维度框架并采用Tobit模型对实时在线评论用户认可度的影响因素进行研究，结果发现：实时在线评论的新颖性、相似性、情感倾向性和信息丰富性，均对实时在线评论的用户认可度存在显著影响，其中新颖性和相似性影响作用最大。视频网站可以据此进一步强化实时在线评论管理，改善用户的体验，保持用户的粘性。     

Exploring gaps in the online economic inclusion of persons with disabilities in Korea

ABSTRACT

This paper explores the difference in the online economic activities of people with and without disabilities in Korea. We conducted a multiple regression analysis to investigate the impact of socioeconomic characteristics, internet access, and internet skills on online economic activities. Our sample, based on a 2016 dataset that included 1554 people with disabilities and 6004 people without disabilities, was developed using quota sampling based on gender, age, and residence. We determined that individuals with disabilities were more likely to engage in online economic activities if they had higher levels of education, lived in urban areas, were employed, or had greater internet skills. Individuals without disabilities were more likely to engage in online economic activities if they were women, had higher levels of education, were employed, lived in a two-generation or more household, or had greater internet skills. For both people with and without disabilities, the level of education, employment status, and internet skills positively contribute to online economic activites. We also determined that education level, participation in economic activity, living in a two-generation or more household, and internet skills had a statistically significant influence on online economic activity for people both with and without disabilities. These results highlight the importance of education and internet training for people with disabilities, as well as social support systems that help them learn to use the internet in diverse ways through both formal and informal networks. The study also underscores the importance of information and communications technology that adequately addresses people’s needs.     

城市治理的基本假设及其幻想

当前关于城市“管理”的理论研究中，“城市治理”的话语正在取代“城市管理”，由此形成的各种对城市的认知也反映在城市的实践中，譬如，提倡提高公众参与、实施精细化治理、信仰信息技术等。通过审视城市治理主张的公众参与假设、技术治理假设和空间治理假设，文章提出治理理论的兴起不足以取代城市管理理论;对管理主义的批评，不能通盘否定“管理”理论对城市的重要作用。主张重塑城市管理理念，以管理思想处理理性与自由的关系，理清并守住政府的职责，警惕唯市场效率，探索多元价值的平衡之道，贡献管理公共性的经验，促进国家治理能力和治理体系的现代化。     

关于企业会计准则改革的若干思考

文章首先回顾了从我国计划经济时期的行业会计制度、改革开放初期引进外资背景下的企业会计制度到1993年企业会计准则体系确立的历史进程。在此基础上,系统总结了企业会计准则在改革发展过程中的主要特征,即与国际会计准则逐渐趋同、母公司报表和合并报表同时披露、以历史成本为主兼顾公允价值。经过20多年的发展,中国逐步建立了符合市场经济要求的、与国际规则趋同的、较为完备的企业会计准则体系,使得相关领域工作者的会计思维实现了从计划经济向市场经济的转变。但现行会计准则还存在一些问题,例如未处理好会计准则制定与会计目标之间关系、部分准则产生了不利的经济后果、未很好地建立会计信息分析方法体系等等。基于上述问题,提出了相应的对策建议。研究结论对中国会计准则改革和会计信息服务实体经济具有积极的启示作用。     

新一代信息技术驱动的产品适应性创新机制

现有产品创新研究多从用户、产品以及技术单一视角出发,然而,进入数字经济时代,在新一代信息技术驱动下,产品以用户、企业、环境多维互动的方式进行创新,呈现出特有的适应性创新特征。本文采取多案例研究方法,探讨在新一代信息技术驱动下产品适应性创新的特征和实现机制。研究发现:产品适应创新具有高频互动、即时反馈、快速适应性和用户主导创新四个显著特征,形成用户、企业、产品多方互动的适应性创新实现机制。与此同时,通过案例论证以产品、场景、用户为核心特征的产品适应创新实现机制的存在性,指出其本质是深入挖掘用户需求并实现用户需求的快速匹配。     

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.     

HDDA: DataSifter: statistical obfuscation of electronic health records and other sensitive datasets

There are no practical and effective mechanisms to share high-dimensional data including sensitive information in various fields like health financial intelligence or socioeconomics without compromising either the utility of the data or exposing private personal or secure organizational information. Excessive scrambling or encoding of the information makes it less useful for modelling or analytical processing. Insufficient preprocessing may compromise sensitive information and introduce a substantial risk for re-identification of individuals by various stratification techniques. To address this problem, we developed a novel statistical obfuscation method (DataSifter) for on-the-fly de-identification of structured and unstructured sensitive high-dimensional data such as clinical data from electronic health records (EHR). DataSifter provides complete administrative control over the balance between risk of data re-identification and preservation of the data information. Simulation results suggest that DataSifter can provide privacy protection while maintaining data utility for different types of outcomes of interest. The application of DataSifter on a large autism dataset provides a realistic demonstration of its promise practical applications.     

The Practical Significance of Measurement Error in Pulmonary Function Testing Conducted in Research Settings

Conventional spirometry produces measurement error by using repeatability criteria (RC) to discard acceptable data and terminating tests early when RC are met. These practices also implicitly assume that there is no variation across maneuvers within each test. This has implications for air pollution regulations that rely on pulmonary function tests to determine adverse effects or set standards. We perform a Monte Carlo simulation of 20,902 tests of forced expiratory volume in 1 second (FEV₁), each with eight maneuvers, for an individual with empirically obtained, plausibly normal pulmonary function. Default coefficients of variation for inter‐ and intratest variability (3% and 6%, respectively) are employed. Measurement error is defined as the difference between results from the conventional protocol and an unconstrained, eight‐maneuver alternative. In the default model, average measurement error is shown to be ～5%. The minimum difference necessary for statistical significance at p < 0.05 for a before/after comparison is shown to be 16%. Meanwhile, the U.S. Environmental Protection Agency has deemed single‐digit percentage decrements in FEV₁ sufficient to justify more stringent national ambient air quality standards. Sensitivity analysis reveals that results are insensitive to intertest variability but highly sensitive to intratest variability. Halving the latter to 3% reduces measurement error by 55%. Increasing it to 9% or 12% increases measurement error by 65% or 125%, respectively. Within‐day FEV₁ differences ≤5% among normal subjects are believed to be clinically insignificant. Therefore, many differences reported as statistically significant are likely to be artifactual. Reliable data are needed to estimate intratest variability for the general population, subpopulations of interest, and research samples. Sensitive subpopulations (e.g., chronic obstructive pulmonary disease or COPD patients, asthmatics, children) are likely to have higher intratest variability, making it more difficult to derive valid statistical inferences about differences observed after treatment or exposure.