二语学术写作引用研究述评

文章从二语习得和二语使用两个视角对二语学术写作引用研究的现状及其成果进行了梳理并发现：学术引用能力是在读写认知过程中逐渐发展起来的,且受到学术写作知识、批判性思维和文本借用策略的影响;引用的类型、修辞功能及其学术语体在专家与新手的学术写作中存在差异。     

A stochastic model of organizational mortality: Review and reanalysis

An effort is made to integrate the research literatures of business policy and organizational sociology as they concern organizational mortality. The previous empirical studies of organizational mortality are reviewed and considered in light of current theoretical arguments. Three stochastic models are developed to test hypotheses concerning organizational mortality: the constant rate model, the Gompertz model, and Makeham's Law. The parameters of these models are estimated for 52 sets of data on organizational mortality. The findings show that Makeham's Law is the best-fitting model, although its estimation requires data with low levels of censoring. Substantively, the findings show strong support for Stinchombe's liability-of-newness hypothesis [A. L. Stinchcombe (1965), “Organizations and social structure,” in Handbook of Organizations (J. G. March, Ed.), pp. 153–193, Rand McNally, Chicago].     

对“中文屋”思想实验四个主要版本的考察

"中文屋"思想实验提出30年来,学界对该思想实验在批判强人工智能的有效性问题上一直争论不休。特别是强人工智能的支持者往往通过转换视角,添加问题或构建新理论模型等方式试图躲避"中文屋"的责难。为应对各种回应,塞尔在保持"中文屋"论证的基本逻辑结构和要点不变的前提下,通过修改思想实验的描述形式进行一一答复,从而保证了该思想实验对强人工智能批判上的效力。借助对"中文屋"几个主要版本及其相关答复的考察,表明"中文屋"在批判强人工智能上的有效性,同时指出这种有效性并不依赖于思想实验外在描述形式的变化,而依赖于蕴含其中的论证结构和论证形式。     

美国私募基金监管法律制度研究及对我国的启示

美国是私募基金最为发达的国家之一。在私募基金发展初期,其对私募基金监管较为宽松。然而,私募基金自身的发展逐渐带来了诸多新问题,如私募股权基金公募化、财务杠杆的大量使用、私募基金私有化上市公司等。2010年,美国通过了《金融监管改革法案》,加强了对私募股权基金的监管。反观我国,私募股权基金在我国已经具有了一定的规模,虽尚不足以产生系统性风险,但有必要从投资者保护角度入手建立健全私募股权基金监管法律制度。     

Part I––Comparing Noncancer Chronic Human Health Reference Values: An Analysis of Science Policy Choices

The goal of this study was to systematically evaluate the choices made in deriving a chronic oral noncancer human health reference value (HHRV) for a given chemical by different organizations, specifically those from the U.S. Environmental Protection Agency, Health Canada, RIVM (the Netherlands), and the U.S. Agency for Toxic Substances and Disease Registry. This analysis presents a methodological approach for comparing both the HHRVs and the specific choices made in the process of deriving an HHRV across these organizations. Overall, across the 96 unique chemicals and 171 two‐way organizational comparisons, the HHRV agreed approximately 26% of the time. A qualitative method for identifying the primary factors influencing these HHRV differences was also developed, using arrays of HHRVs across organizations for the same chemical. The primary factors identified were disagreement on the critical or principal study and differential application of the total uncertainty factor across organizations. Of the cases where the total UF was the primary factor influencing HHRV disagreement, the database UF had the greatest influence.     

Part II: Quantitative Evaluation of Choices Used in Setting Noncancer Chronic Human Health Reference Values Across Organizations

Environmental and public health organizations, including the World Health Organization (WHO) and the U.S. Environmental Protection Agency (USEPA), develop human health reference values (HHRV) that set “safe” levels of exposure to noncarcinogens. Here, we systematically analyze chronic HHRVs from four organizations: USEPA, Health Canada, RIVM (the Netherlands), and the U.S. Agency for Toxic Substances and Disease Registry. This study is an extension of our earlier work and both closely examines the choices made in setting HHRVs and presents a quantitative method for identifying the primary factors influencing HHRV agreement or disagreement.⁽¹⁾ We evaluated 171 organizational comparisons, developing a quantitative method for identifying the factors to which HHRV agreement (that is, when both organizations considering the same data set the identical HHRV values) is most sensitive. To conduct this analysis, a Bayesian belief network was built using expert judgment, including the specific science policy choices analysis made in the context of setting an HHRV. Based on a sensitivity of findings analysis, HHRV agreement is most sensitive to the point of departure value, followed by the total uncertainty factor (UF), critical study, critical effect, animal model, and point of departure approach. This analysis also considered the specific impacts of individual UFs, with the database UF and the subchronic‐to‐chronic UF being identified as primary factors impacting the total UF differences observed across organizations. The sensitivity of findings analysis results were strengthened and confirmed by frequency analyses evaluating which choices most often disagreed when the HHRV and the total UF disagreed.     

也谈参考文献的作用及其引用问题

参考文献是论文的重要组成部分。认为参考文献有六方面的作用,提出了参考文献的引用原则,并就当前参考文献的引用问题进行了分析。     

Noninformative priors for the generalized half-normal distribution

In this paper, we develop noninformative priors for the generalized half-normal distribution when scale and shape parameters are of interest, respectively. Especially, we develop the first and second order matching priors for both parameters. For the shape parameter, we reveal that the second order matching prior is a highest posterior density (HPD) matching prior and a cumulative distribution function (CDF) matching prior. In addition, it matches the alternative coverage probabilities up to the second order. For the scale parameter, we reveal that the second order matching prior is neither a HPD matching prior nor a CDF matching prior. Also, it does not match the alternative coverage probabilities up to the second order. For both parameters, we present that the one-at-a-time reference prior is a second order matching prior. However, Jeffreys’ prior is neither a first nor a second order matching prior. Methods are illustrated with both a simulation study and a real data set.     

Analysis of Frechet Distribution Using Reference Priors

This article develops the Bayesian estimators in the context of reference priors for the two-parameter Frechet distribution. The general forms of the second-order matching priors are also derived in case of any parameter of interest and concluded that the reference prior is also a second order matching prior. Since the Bayesian estimators cannot be obtained in closed form, they are obtained using Monte Carlo simulation and Laplace approximation. The Bayesian and maximum likelihood estimates are compared via simulation study. Two real-life data sets are analyzed for illustration and comparison purpose.     

Intrinsic Bayesian inference on a Poisson rate and on the ratio of two Poisson rates

Our purpose is to explore the intrinsic Bayesian inference on the rate of a Poisson distribution and on the ratio of the rates of two independent Poisson distributions, with the natural conjugate family of priors in the first case and the semi-conjugate family of priors defined by Laurent and Legrand (2011) in the second case. Intrinsic Bayesian inference is derived from the Bayesian decision theory framework based on the intrinsic discrepancy loss function. We cover in particular the case of some objective Bayesian procedures suggested by Bernardo when considering reference priors.