非抽样误差问题研究

在考察国内外非抽样误差分类的基础上，指出按产生非抽样误差的直接原因分类是比较科学的。非抽样误差可分为6类：概率抽样偏差、样本估计偏差、范围偏差、无回答偏差、回答偏差、数据的抄写等偏差。产生这些误差的原因及相应的对策。     

不同检测系统总胆固醇、甘油三酯测定的对比分析

通过对不同检测系统进行方法对比分析,探讨各系统之间检测总胆固醇(TCHOL)、甘油三酯(TG)结果是否具有可比性。参照NCCLS《EP9-A文件》的要求,以可溯源的检测系统为目标检测系统,均采用酶法测定TCHOL、TG,对本院3个不同检测系统进行朗道质控物(水平2和水平3)各测定21次和测定新鲜血清标本40份。朗道质控物和新鲜血清标本TCHOL、TG测定经随机区组设计资料的方差分析,各检测系统间的差异均有显著性(P<0.001)。各检测系统测定新鲜血清标本TCHOL、TG可靠性系数α分别为0.9977、0.9990,各系统间的相关系数均大于0.975。各检测系统测定TCHOL、TG的精密度CV均小于5%,以可溯源的检测系统1为目标检测系统,临床可接受性能评价TG检测系统2和系统3均未超出临床接受范围,而TCHOL均超出临床接受范围。3个不同检测系统测定TG结果具有可比性;而TCHOL结果不具有可比性,需采取整改措施。当同一实验室同一检验项目存在二个以上的检测系统时,应进行方法比对和偏倚评估。     

从行为地理的角度看台湾当局日本情结的由来

建国以来,台湾与大陆关系的发展,始终是我国各届政府关注的焦点。全面地看待台湾回归问题,可以发现影响这一问题解决的因素不仅表现在台海内部,而且明显的受到国际因素的左右。几十年来,台湾当局始终在不断地拓展自身的外部生存空间,在这一过程中,日本成为台湾当局倍加青睐的对象。本文将从行为地理的角度解读台湾的日本情结,以地理物象为基础,通过对时空的综合分析,以行为地理学的研究方法粗浅的谈一下这种情结的由来。     

父母对幼儿行为问题反应偏向的原因及影响分析

通过对上海市四家幼儿园86名幼儿父母进行有关儿童行为问题家长评定的调查,发现父母评定的儿童行为问题的比率极其显著高于专家和专业研究机构的判定比率。家长的这一反应偏向可能与他们缺乏相关科学知识、对孩子的高期望以及中国传统文化有关,并可能导致产生育儿焦虑及不当的教养行为,从而对早期家庭教育产生负面影响。     

Personality similarity between teachers and their students influences teacher judgement of student achievement

This study examined personality similarity between teachers and their students and its impact on teacher judgement of student achievement in the domains of reading comprehension and mathematics. Personality similarity was quantified through intraclass correlations between personality characteristics of 409 dyads of German teachers and their students. This similarity index was combined with teachers’ global and task-specific judgements of student achievement. Personality similarity has a significant effect on global judgement in both domains under study. Students who are similar to their teacher are judged more positively than students who are dissimilar, even when students’ test performance is controlled. This effect could not be verified for task-specific judgements. Results indicate that impact of potential sympathy bias in social judgements differs between different types of judgement. That is, global judgements are more likely to be biased than more specific judgements. Theoretical and educational relevance of the findings are discussed.     

Multilevel Modeling and Ordinary Least Squares Regression: How Comparable Are They?

Studies analyzing clustered data sets using both multilevel models (MLMs) and ordinary least squares (OLS) regression have generally concluded that resulting point estimates, but not the standard errors, are comparable with each other. However, the accuracy of the estimates of OLS models is important to consider, as several alternative techniques (e.g., bootstrapping) used when analyzing clustered data sets only make adjustments to standard errors but not to the regression coefficients. Using a Monte Carlo simulation, we analyzed 54,000 data sets using both MLM and OLS under varying conditions and we show that coefficients of not just OLS models, but MLMs as well, may be biased when relevant higher-level variables are omitted from a model, a situation that is likely to occur when using large-scale, secondary data sets. However, we demonstrate that by including aggregated level-one variables at the higher level, the resulting bias can be effectively removed.     

从"偏见观"看译者的创造性叛逆

本文从伽达默尔哲学阐释学理解的历史性和偏见观的概念着手,分析在翻译活动中作为阐释者的译者对原作的创造性叛逆这一客观现象的合理性和不可避免性,指出译者的主体性应得到重视。     

Model Mis-Specification In Assessing The Impact of Financial Aid on Academic Outcomes

The focus of the paper is the development of a novel conceptual framework that aims to remedy a critical mis-specification in prior research on the impact of financial aid on academic outcomes: the blending of the effect of aid eligibility with the influence of aid amounts on academic outcomes. To assess the impact of aid amounts received on college graduation while considering aid receipt status as an endogenous variable, I use the procedure of Instrumental Variable Probit. Empirical illustration of this model confirms that the interrelationships between aid eligibility and graduation mask the positive impact of financial aid on graduation.     

社会认知偏差对管理活动的影响

领导者如何在发现和激励人才等关键环节有效地避免不利于生产经营活动的社会认知偏差,使有利于提高管理水平和促进沟通的社会认知偏差充分发挥作用,对企业的发展利害攸关.研究表明,一些常见的社会认知偏差,如晕轮效应、刻板印象、首因效应、透明度错觉等,在人员的选拔和任用中既能产生消极的影响,又能产生积极的影响.     

人工智能算法歧视及其治理

人工智能的快速崛起,在人类事务领域引发无法想象的革命的同时,愈益严重的算法歧视现象也引发了人们普遍的担忧与焦虑。AI算法绝不仅仅是一项单纯的技术性问题,其蕴含的政治风险、安全风险与伦理道德风险同样不容忽视。实际上,算法歧视不仅会导致种族歧视、性别歧视等严重社会后果,在一些关键领域或特定情境下,还会侵害公民权利、自由,甚至危害其生命安全。因此,对算法歧视善加治理,才能为算法及其行业的健康发展创造良好的环境。