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.     

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.     

Multiple event times in the presence of informative censoring: modeling and analysis by copulas

Motivated by a breast cancer research program, this paper is concerned with the joint survivor function of multiple event times when their observations are subject to informative censoring caused by a terminating event. We formulate the correlation of the multiple event times together with the time to the terminating event by an Archimedean copula to account for the informative censoring. Adapting the widely used two-stage procedure under a copula model, we propose an easy-to-implement pseudo-likelihood based procedure for estimating the model parameters. The approach yields a new estimator for the marginal distribution of a single event time with semicompeting-risks data. We conduct both asymptotics and simulation studies to examine the proposed approach in consistency, efficiency, and robustness. Data from the breast cancer program are employed to illustrate this research.

     

理智与情感:为历史“正名”的方法——从刘保昌长篇小说《楚武王》谈起

历史书写中的“最炫流行风”在今天的文化市场上大行其道——用拆解、谐谑、碎片化、戏拟等方式拉平历史的深度,以“傲慢与偏见”来充抵叙述历史的自信,也经由这种时尚化的叙述使历史以“轻松一刻”的形式实现消费欲望的满足.刘保昌的《楚武王》则疏离“流行前线”,以史料为据,正本清源,守正而出新,为历史“正名”,以彰显历史意识、历史理性的写作姿态,以坚持文学之理想力量的叙事激情,以有文化承担的叙事态度显示出对当代历史小说叙事品格与尊严的坚守.     

A modified common factor model for modelling mortality jointly for both sexes

Journal of Population Research - There is an increasing attention on the joint modelling of multiple populations. Populations are related in several ways, such as neighbouring countries, females...     

1950年代:“本质—特征论”文学定义的形成及影响

1950年代形成了"本质—特征论"的文学定义,即先界定文学的意识形态本质,再界定文学是用形象的方式来反映社会生活、体现意识形态的特征。这一定义的思维方式是先界定事物的普遍性,再界定事物的特殊性,突出事物的普遍性关联,轻视事物的独特性质的揭示,使得文学研究本应着重研究文学的特殊性成为空话,不利于认识文学自身的规律。1980年代的文学审美论试图突破这种定义方式,但1990年代以来,反本质主义的文学语境论再次回到从事物的关联性定义事物的思维老路,文学自身本质问题受到质疑,弱化了文学与审美关联的重要性与必要性。     

Partial Identification of Economic Mobility: With an Application to the United States

Abstract

The economic mobility of individuals and households is of fundamental interest. While many measures of economic mobility exist, reliance on transition matrices remains pervasive due to simplicity and ease of interpretation. However, estimation of transition matrices is complicated by the well-acknowledged problem of measurement error in self-reported and even administrative data. Existing methods of addressing measurement error are complex, rely on numerous strong assumptions, and often require data from more than two periods. In this article, we investigate what can be learned about economic mobility as measured via transition matrices while formally accounting for measurement error in a reasonably transparent manner. To do so, we develop a nonparametric partial identification approach to bound transition probabilities under various assumptions on the measurement error and mobility processes. This approach is applied to panel data from the United States to explore short-run mobility before and after the Great Recession.     

高含水期油藏层间压力结构差异量化方法研究

由于长期注水开发和层间非均质性影响，高含水期油藏各小层层间压力结构差异严重，掌握差异状况是合理调整的重要依据。针对现场分层测压资料少，单层压力资料获取困难的情况，应用渗流力学原理建立了高含水期地层层间压力结构差异量化数学模型，模型的关键参数可以通过生产数据计算获得。枣园油田的实例验证表明，高含水油藏层间压力存在明显差异，该方法能够确定各小层的压力差异状况。量化计算结果和实测资料相接近，有利于认清开发矛盾，为合理调整提供技术依据。     

试述新中国成立初期中共干部的专业教育

新中国成立初期,中国共产党专业干部队伍基础十分薄弱,不仅数量少,总体质量也不高,成为国家发展建设中的巨大瓶颈。为此,中国共产党迅速采取措施,大力加强专业干部队伍建设,其重要举措之一是广泛开展干部的专业教育。这一时期干部专业教育主要通过三种途径:创办专业干部学校、紧紧依托高等院校、举办各种专业讲座和短期培训班等。由于党和人民政府高度重视、精心组织和大力推动,干部专业教育取得了显著成效,不仅迅速提高了广大干部的专业水平和业务能力,满足国家发展建设的需要,并且对中共干部队伍建设产生了深远影响。     

Towards Uniformly Efficient Trend Estimation Under Weak/Strong Correlation and Non‐stationary Volatility

In this paper, we consider the deterministic trend model where the error process is allowed to be weakly or strongly correlated and subject to non‐stationary volatility. Extant estimators of the trend coefficient are analysed. We find that under heteroskedasticity, the Cochrane–Orcutt‐type estimator (with some initial condition) could be less efficient than Ordinary Least Squares (OLS) when the process is highly persistent, whereas it is asymptotically equivalent to OLS when the process is less persistent. An efficient non‐parametrically weighted Cochrane–Orcutt‐type estimator is then proposed. The efficiency is uniform over weak or strong serial correlation and non‐stationary volatility of unknown form. The feasible estimator relies on non‐parametric estimation of the volatility function, and the asymptotic theory is provided. We use the data‐dependent smoothing bandwidth that can automatically adjust for the strength of non‐stationarity in volatilities. The implementation does not require pretesting persistence of the process or specification of non‐stationary volatility. Finite‐sample evaluation via simulations and an empirical application demonstrates the good performance of proposed estimators.