汉代乐舞中的人本主义精神探析

在我国长达3000多年的乐舞文化中,汉代乐舞以其张扬阔大、发扬蹈厉的强悍风格独树一帜,堪称中华乐舞史的最强音.造就强汉之音的精神底座,是在秦汉代际蓬勃兴起的人本主义精神.从汉武时期乐制的更作和乐府制度的确立,到盛行两汉的乐舞形制,再到志尽于诗、音尽于曲的乐舞歌诗和意气相尚、悲歌厉响的审美取向,无不反映并凸显着人本主义精神的光辉.在我国当下民族复兴的进程中,人本主义精神同样应成为时代诉求.     

“功能性表达性模型”与中国警察信任——基于全国样本的多重中介与调节模型分析

功能性模型认为，提升警察信任的主要方法在于预防和控制犯罪，降低犯罪率与提升公众安全感；而表达性模型认为，提升警察信任更应注重维护社会正义与社区凝聚力。基于提出促进中国警察信任度提高的理论模型，提升公众获得感、幸福感、安全感，实现国家和社会整体安全的最终目的，采用结构方程模型验证“功能性-表达性模型”与中国警察信任关系的结果表明，功能性模型与表达性模型内部因素之间存在显著路径关系，同时功能性模型显著影响表达性模型指标进而改变公众对警察的信任程度。经调节效应分析后发现，主观社会阶层负向调节被害经历到犯罪恐惧感的直接路径，社交媒体使用负向调节犯罪恐惧感到警察信任的直接路径；在主观社会阶层和社交媒体使用的共同调节作用下，“被害经历→犯罪恐惧感→警察信任”中介路径效应值，随社交媒体使用频率的提升而增大，随主观社会阶层的升高而减小。     

网络民族志基于研究者身份的伦理关系

民族志一度是研究者专业生产他者知识的手段与途径,但在反思传统与顺应新潮流——互联网的基础上,我们发现,一直以来研究者自己也是民族志的研究对象,互联网兴起之后,这种倾向更加明显.网络时代的到来促使研究者的身份发生了显著转变:由自己是主体,被研究者是他者,转变为双方是平等的交互主体;由认识主体转变为实践主体;由主动的实践者转变为静默的潜伏者等.网络民族志中研究者身份的变化,为新的研究伦理关系的出现开辟了道路,即研究者与被研究者既是学术研究的手段,也是学术研究的目的.     

Noninformative priors for the between-group variance in the unbalanced one-way random effects model with heterogeneous error variances

For the unbalanced one-way random effects model with heterogeneous error variances, we propose the non-informative priors for the between-group variance and develop the first- and second-order matching priors. It turns out that the second-order matching priors do not exist and the reference prior and Jeffreys prior do not satisfy a first-order matching criterion. We also show that the first-order matching prior meets the frequentist target coverage probabilities much better than the Jeffreys prior and reference prior through simulation study, and the Bayesian credible intervals based on the matching prior and reference prior give shorter intervals than the existing confidence intervals by examples.     

Regression analysis of case-cohort studies in the presence of dependent interval censoring

The case-cohort design is widely used as a means of reducing the cost in large cohort studies, especially when the disease rate is low and covariate measurements may be expensive, and has been discussed by many authors. In this paper, we discuss regression analysis of case-cohort studies that produce interval-censored failure time with dependent censoring, a situation for which there does not seem to exist an established approach. For inference, a sieve inverse probability weighting estimation procedure is developed with the use of Bernstein polynomials to approximate the unknown baseline cumulative hazard functions. The proposed estimators are shown to be consistent and the asymptotic normality of the resulting regression parameter estimators is established. A simulation study is conducted to assess the finite sample properties of the proposed approach and indicates that it works well in practical situations. The proposed method is applied to an HIV/AIDS case-cohort study that motivated this investigation.     

A primal dual active set with continuation algorithm for high-dimensional nonconvex SICA-penalized regression

The smooth integration of counting and absolute deviation (SICA) penalty has been demonstrated theoretically and practically to be effective in nonconvex penalization for variable selection and parameter estimation. However, solving the nonconvex optimization problem associated with SICA penalty in high-dimensional setting remains to be enriched, mainly due to the singularity at the origin and the nonconvexity of the SICA penalty function. In this paper, we develop a fast primal dual active set (PDAS) with continuation algorithm for solving the nonconvex SICA-penalized least squares in high dimensions. Upon introducing the dual variable, the PDAS algorithm iteratively identify and update the active set in the optimization using both the primal and dual information, and then solve a low-dimensional least square problem on the active set. When combined with a continuation strategy and a high-dimensional Bayesian information criterion (BIC) selector on the tuning parameters, the proposed algorithm is very efficient and accurate. Extensive simulation studies and analysis of a high-dimensional microarray gene expression data are presented to illustrate the performance of the proposed method.     

Reviews of Academic English Listening Tests for Non-Native Speakers

This article presents a review of 20 tests designed for assessing the academic English listening skill of second or foreign language learners. The available test information has been systematically condensed in purpose, listening construct, task characteristics, and validity evidence. It was found that most of the tests were developed for proficiency and placement purposes in academic contexts, with few of the tests serving for making workplace decisions. Also, global, local, and inferential skills constitute the construct in most listening comprehension tests. A practical approach for justifying the uses of these tests for different stakeholders is discussed. This review is a valuable resource for educators, administrators, test developers, and researchers looking for a comprehensive analysis of existing English tests that assess listening comprehension in second or foreign language learners.     

西方经济学话语特征与中国经济学话语体系建设

长期以来,经济学理论总是笼罩在西方中心论的西方主流经济学话语体系下,既不能解释真实世界变化,也无力为乏力的世界经济开出药方。中国改革开放40多年以来,经济增长取得举世瞩目的成就,而西方经济学的理论却无法解释中国经济发展的奇迹。总结中国改革开放伟大成功的经验,就在于不受西方经济学理论的影响,始终坚定不移地走好中国特色社会主义道路。中国实践的成功已经打破了西方中心论的"神话",但尚未形成一套系统的、完整的、严谨的中国经济学理论体系。因此,构建中国经济学话语体系是系统化总结中国发展经验的内在理论诉求。基于此,本文在厘清西方经济学话语特征基础上,提出中国经济学话语体系建设要突出国家主体性、阐释好中国道路、服务于国家战略。     

基于大数据合作资产的适应性创新--数字经济的创新逻辑(二)

万物互联时代,数据被认为是与土地、劳动、资本、知识、技术和管理并重的第七大生产要素。当前,多样化的商业实践创新对数据价值的深度挖掘正在突破经济学在传统意义上对数据及其价值的限定,然而,理论上对此还缺乏相应的概念凝练和探讨。本文从企业与消费者价值共创角度提出大数据合作资产的概念,并探讨基于大数据合作资产和适应性创新的数字经济创新逻辑。研究表明:大数据合作资产是一种互动性资源,是企业与消费者在数字化服务交互中成为能够被另一方所拥有和利用并能创造当前或未来经济收益的数字化资产;单纯拥有异质资源不一定会形成合作资产,只有当异质化资源被有效整合、且被使用于企业与消费者服务交换中,才能体现为行动者创造收益的价值潜力;协同演化促进了企业与消费者对彼此的适应性调整,基于大数据合作资产激发以即时调整、即时反馈和难以预测为特征的适应性创新,进而促进了数字经济创新。