Marriage and gender inequality: work–family arrangements of Portuguese and British highly qualified women

This article examines work–family reconciliation processes in order to understand if, over the course of marital life, women become socially closer or further away from their partner. Drawing on work–life interviews with highly qualified women in Portugal and Britain, we compare these processes in two societies with different historical and social backgrounds. Findings reveal three main configurations of social (in)equality which emerge during married life: growing inequality in favour of the man, in favour of the woman or equality between spouses. With due attention to the importance of national specific factors, we present three main conclusions. First, (in) equality is built up over the course of marital life and female strategies for reconciling family and work are at the core of this process. Second, the national specificities can mould the effects of cross-national gender mechanisms. Third, the intersection between cross-cultural phenomena such as conservative attitudes towards domestic work and national specificities (such as the availability of part-time options) is a rather complex process which needs further research.     

德国项目教学法在高职教学中的实践与创新

项目教学法是德国＂双元制＂职业院校中盛行的教学模式,但多用于工科专业。自引入我国以来,对于工科类高职院校来说,效果非常明显,但对于财经类专业应用效果不尽人意。本文选取财经类专业岗位财务管理岗位实际工作情境之一——筹资,以项目教学法为基础,构建了包括教学情境的设计、学生学习步骤一览表的制定、学生学习步骤计划书的设计、学生自我测试及测试题库的设计、工作任务的设计、参考信息的提供、学习方法和策略的指导、项目成果的展示要求、教学评价方法的制定共9个部分组成的课堂教学体系。     

阶梯电价背景下基于贝叶斯分析的用电需求模型

阶梯电价不仅引导居民合理、节约用电,而且减少了用户之间的电价交叉补贴,但在实际应用中存在多种不确定因素,如居民用电需求变动以及各档电量的确定范围等。针对居民用电需求变动,本文提出了基于贝叶斯估计方法的阶梯电价用电需求模型。首先提出基于阶梯电价的需求函数;其次对阶梯电价用电需求函数进行贝叶斯分析,分别从统计模型、似然函数、后验分布以及加速收敛四个方面分析;最后,对1250个用户的用电数据进行估计,将影响因素带入模型得出各用户的用电需求,确定了贝叶斯估计对用电需求模型构建的适用性。     

Measures of accountability and delegated discretion in activation work: lessons from the Norwegian Labour and Welfare Service

Activation work – the complex task of motivating, compelling and assisting marginalized citizens into labour market participation – pinpoints critical issues of discretion and accountability in the welfare state. Investigating accountability measures aimed at ensuring qualified discretionary judgements is therefore important. In this article, I discuss the reformed Norwegian Labour and Welfare Service and the accountability measures aimed at discretionary judgements of frontline workers. The conclusion is that, because activation tasks in the Norwegian frontline service imply professional discretion more than administrative discretion, structural measures aimed at restricting the discretionary space of frontline workers seem to have only limited impact. This is because the knowledge necessary to perform means – end judgements is insufficient. Rather, there seems to be a need for epistemic measures aimed at improving the knowledge base for professional discretionary reasoning.     

将生命还给社会:传记法作为一种总体叙事方式

在田野民族志和历史编纂学中，传记法是一种重要的叙事方式。本文从分析林耀华的作品入手，将其置于20世纪20年代以来的社会学和人类学思想脉络中，并在此基础上探讨传记法在中国历史和社会研究中的潜力与可能性。本文将谱系法、个人生命史和社会生命论归纳为“传记法三角”。在（扩展）谱系法和社会结构论的基础上，生命传记法可以呈现一个或多个人的生命历史，作为大历史中的片段。不过，现象学路径有其自身的限度，不能离开对中央政权本身和总体结构的考察。在“时势”和“社会结构”的变迁过程中呈现生命传记，才不会只是个体的故事，而有希望成为一种对中国“总体”社会生活的有力叙事方式。     

A new algorithm for clustering based on kernel density estimation

In this paper, we present an algorithm for clustering based on univariate kernel density estimation, named ClusterKDE. It consists of an iterative procedure that in each step a new cluster is obtained by minimizing a smooth kernel function. Although in our applications we have used the univariate Gaussian kernel, any smooth kernel function can be used. The proposed algorithm has the advantage of not requiring a priori the number of cluster. Furthermore, the ClusterKDE algorithm is very simple, easy to implement, well-defined and stops in a finite number of steps, namely, it always converges independently of the initial point. We also illustrate our findings by numerical experiments which are obtained when our algorithm is implemented in the software Matlab and applied to practical applications. The results indicate that the ClusterKDE algorithm is competitive and fast when compared with the well-known Clusterdata and K-means algorithms, used by Matlab to clustering data.     

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.     

A robust automatic clustering algorithm for probability density functions with application to categorizing color images

This study develops a robust automatic algorithm for clustering probability density functions based on the previous research. Unlike other existing methods that often pre-determine the number of clusters, this method can self-organize data groups based on the original data structure. The proposed clustering method is also robust in regards to noise. Three examples of synthetic data and a real-world COREL dataset are utilized to illustrate the accurateness and effectiveness of the proposed approach.     

Several least-squares problems related to the Hodrick–Prescott filtering

The Hodrick–Prescott (HP) filtering is frequently used in macroeconometrics to decompose time series, such as real gross domestic product, into their trend and cyclical components. Because the HP filtering is a basic econometric tool, it is necessary to have a precise understanding of the nature of it. This article contributes to the literature by listing several (penalized) least-squares problems that are related to the HP filtering, three of which are newly introduced in the article, and showing their properties. We also remark on their generalization.     

Non uniform exponential bounds on normal approximation by Stein’s method and monotone size bias couplings

It is known that the normal approximation is applicable for sums of non negative random variables, W, with the commonly employed couplings. In this work, we use the Stein’s method to obtain a general theorem of non uniform exponential bound on normal approximation base on monotone size bias couplings of W. Applications of the main result to give the bound on normal approximation for binomial random variable, the number of bulbs on at the terminal time in the lightbulb process, and the number of m runs are also provided.