明代小说中寄生词曲与社会生活

明代小说中寄生词曲为明代社会生活之镜像。寄生词曲中最为常见而又特色突出的社会生活描写主要在服饰生活、饮食生活、居住生活、娱乐生活等方面,以此可以窥明代社会生活之全貌。探讨明代小说中寄生词曲与社会生活之关系,有助于深化明代词曲和明代社会生活史的研究。     

A decade after the Reform: political activism of the Chinese of West Kalimantan,Indonesia

Political reform after the departure of President Soeharto’s New Order (1966–1998) provided opportunities for previously oppressed social groups to express their concerns and to demand fair recognition. The results of this newly found freedom have been quite immediately visible in Jakarta, where social and political institutions spearheaded by Chinese originally sprouted. In the regions, political participation of ethnic Chinese has also grown; significantly in those regions with a large Chinese population. In West Kalimantan, the number of Chinese being elected to local parliaments in some regions has doubled. They have also contested numerous direct local executive elections since 2003 and have been successful in winning four posts: a mayor, a district head, a deputy district head, and a deputy governor. By looking at the case of West Kalimantan, this article will examine the factors behind the growth in Chinese political activism, the factors contributing to the success of Chinese candidates in elections, how the Chinese have influenced local and provincial politics, and the challenges they are facing.     

Estimation and diagnostic analysis in skew-generalized-normal regression models

The skew-generalized-normal distribution [Arellano-Valle, RB, Gómez, HW, Quintana, FA. A new class of skew-normal distributions. Comm Statist Theory Methods 2004;33(7):1465–1480] is a class of asymmetric normal distributions, which contains the normal and skew-normal distributions as special cases. The main virtues of this distribution is that it is easy to simulate from and it also supplies a genuine expectation–maximization (EM) algorithm for maximum likelihood estimation. In this paper, we extend the EM algorithm for linear regression models assuming skew-generalized-normal random errors and we develop a diagnostics analyses via local influence and generalized leverage, following Zhu and Lee's approach. This is because Cook's well-known approach would be more complicated to use to obtain measures of local influence. Finally, results obtained for a real data set are reported, illustrating the usefulness of the proposed method.     

Spatially Balanced Sampling of Continuous Populations

When sampling from a continuous population (or distribution), we often want a rather small sample due to some cost attached to processing the sample or to collecting information in the field. Moreover, a probability sample that allows for design‐based statistical inference is often desired. Given these requirements, we want to reduce the sampling variance of the Horvitz–Thompson estimator as much as possible. To achieve this, we introduce different approaches to using the local pivotal method for selecting well‐spread samples from multidimensional continuous populations. The results of a simulation study clearly indicate that we succeed in selecting spatially balanced samples and improve the efficiency of the Horvitz–Thompson estimator.     

我国学前教育地方立法研究

学前教育地方立法是我国学前教育立法体系的有机组成部分，截至2020 年1 月，我国现行有效的学前教育地方性法规 规章共61 部，呈现出立法时间跨度大，立法主体覆盖面广，立法模式体例多样等特征。地方立法一定程度上规范着地方学前 教育的有序开展，但也存在部分省市立法机关对当地学前教育立法关注度不高、部分立法难以满足当前学前教育发展需求、表 达不规范、可操作性欠佳、缺乏地方特色以及冲突与越位等问题。对此，应从科学确定学前教育地方立法内容、建立地方性法 律适时更新制度、健全学前教育地方立法调研制度、加强地方立法专业化制度建设等方面予以优化。     

土地流转中为什么会形成大量小农复制

土地流转是实现规模化经营的前提之一,然而土地流转中却出现大量小农复制,从而影响土地流转的质量和效果。运用12省(自治区)2 553份农户问卷,详细分析土地流转中小农复制的现状及其形成原因。研究发现：(1)农户流转耕地面积不大,转入户流转面积20亩及以下的约占总转入户数的60.3％,转出户流转面积5亩及以下的约占总转出户数的74.38％,转出户中仍然经营土地的约占总转出户数的74％。(2)农业分工发达使生产更加方便、文化传统形成路径依赖、禀赋效应产生“价值幻觉”以及公共服务不健全使未来存在不确定性导致转出户流转部分土地。乡土社会限制土地流转范围和经营风险增加风险感知导致转入户流转小规模土地。     

新时代应用型教师的培养：问题与策略——以地方本科院校为视角

以校地合作、校企合作为发展战略的地方本科院校向应用型院校转变，已经成为一种潮流和趋势，而应用型教师的建设与培养更是迫在眉睫。在明确新时代高校应用型教师培养的必要性的基础上，从数量层面、结构层面、能力层面以及培训层面指出了培养过程中存在的问题，同时针对这些问题提出较为有效的应对策略。     

中国台湾地区幼儿园乡土教学研究进展及未来展望

幼儿期是人生发展的关键时期，对幼儿进行乡土教育具有重要的文化传承意义。如何在幼儿园进行乡土教学也是一个值得研究的重要问题。台湾地区幼儿园乡土教学开展近三十年，在乡土教学的课程模式和个案实施方面具有了丰富的研究经验未来可以扩展乡土教学资源研究、加强乡土教学研究历程之间的衔接、开展行动研究编订乡土教材、加强乡土教学参与人员乡土认知的研究，进一步深化幼儿园乡土教学研究。     

Influential observations in GARCH models

This paper examines local influence assessment in generalized autoregressive conditional heteroscesdasticity models with Gaussian and Student-t errors, where influence is examined via the likelihood displacement. The analysis of local influence is discussed under three perturbation schemes: data perturbation, innovative model perturbation and additive model perturbation. For each case, expressions for slope and curvature diagnostics are derived. Monte Carlo experiments are presented to determine the threshold values for locating influential observations. The empirical study of daily returns of the New York Stock Exchange composite index shows that local influence analysis is a useful technique for detecting influential observations; most of the observations detected as influential are associated with historical shocks in the market. Finally, based on this empirical study and the analysis of simulated data, some advice is given on how to use the discussed methodology.     

BUSDM – an algorithm for the bottom-up search of departures from a model

Searching for regions of the input space where a statistical model is inappropriate is useful in many applications. The study proposes an algorithm for finding local departures from a regression-type prediction model. The algorithm returns low-dimensional hypercubes where the average prediction error clearly departs from zero. The study describes the developed algorithm, and shows successful applications on the simulated and real data from the steel plate production. The algorithms that have been originally developed for searching regions of the high-response value from the input space are reviewed and considered as alternative methods for locating model departures. The proposed algorithm succeeds in locating the model departure regions better than the compared alternatives. The algorithm can be utilized in sequential follow-up of a model as time goes along and new data are observed.