Analysis of child labour in Peru and Pakistan: A comparative study

This paper analyses child labour participation and its key determinants using data sets from Peru and Pakistan. The results include tests of the ‘Luxury’ and ‘Substitution’ hypotheses that play key roles in recent studies on child labour and child schooling. The results reject both hypotheses in the context of child labour in Pakistan and suggest that income and related variables do not have the expected negative effect on children's work input. Rising wages of adult female labour in Pakistan, and falling adult male wage in Peru lead to increased participation of children in the labour market. The results on the combined country data formally establish the presence of strong individual country effects in the estimated regressions. For example, ceteris paribus, a Peruvian child is more likely to experience schooling than a Pakistani child. However, both countries agree on the positive role that adult female education and infrastructure investment in basic amenities can play in discouraging child labour and encouraging child schooling. Received: 24 August 1998/Accepted: 10 March 1999     

Personal income taxation under mobility, exogenous and endogenous welfare weights, and asymmetric information

This paper analyses how governments should tax labour income accruing to a group of highly skilled and geographically mobile individuals who divide their time or career between several jurisdictions. The analysis differs from previous models on migration and taxation by addressing optimal regulation when agents work for several principals. Optimal taxation is developed for social welfare functions with exogenous and endogenous welfare weights. Marginal income taxes are applied for screening purposes, and the rates are lower with endogenous than with exogenous welfare weights. Received: 22 January 1998/Accepted: 3 July 1999)     

从《爬行纲分类》课件开发中探讨CAI课件的设计和创作策略

通过对MCAI课件《爬行纲分类》的制作,探讨了在设计MCAI课件时所需要注意的问题。     

Classification with minimum ambiguity under distribution heterogeneity

The traditional classification is based on the assumption that distribution of indicator variable X in one class is homogeneous. However, when data in one class comes from heterogeneous distribution, the likelihood ratio of two classes is not unique. In this paper, we construct the classification via an ambiguity criterion for the case of distribution heterogeneity of X in a single class. The separated historical data in each situation are used to estimate the thresholds respectively. The final boundary is chosen as the maximum and minimum thresholds from all situations. Our approach obtains the minimum ambiguity with a high classification accuracy allowing for a precise decision. In addition, nonparametric estimation of the classification region and theoretical properties are derived. Simulation study and real data analysis are reported to demonstrate the effectiveness of our method.     

A reflected feature space for CART

We present an algorithm for learning oblique decision trees, called HHCART(G). Our decision tree combines learning concepts from two classification trees, HHCART and Geometric Decision Tree (GDT). HHCART(G) is a simplified HHCART algorithm that uses linear structure in the training examples, captured by a modified GDT angle bisector, to define splitting directions. At each node, we reflect the training examples with respect to the modified angle bisector to align this linear structure with the coordinate axes. Searching axis parallel splits in this reflected feature space provides an efficient and effective way of finding oblique splits in the original feature space. Our method is much simpler than HHCART because it only considers one reflected feature space for node splitting. HHCART considers multiple reflected feature spaces for node splitting making it more computationally intensive to build. Experimental results show that HHCART(G) is an effective classifier, producing compact trees with similar or better results than several other decision trees, including GDT and HHCART trees.     

现行高校分类模式:局限与超越

在对目前高校分类进行考察的基础上,指出现行高校分类模式存在着层次与类型混淆、科研与教学对立、重点与类型匹配、学制与类型挂钩等弊端。提出了高校类型划分的社会功能视角,将高等学校划分为:学术型高校、行业型高校和职业型高校。     

英语写作策略分类探讨

英语写作策略分类研究是一个基础研究课题,对英语写作研究及写作教学实践具有实际价值和现实意义。本文分析了目前研究中的英语写作策略分类存在的问题,并回顾了英语写作及策略的相关理论,提出了英语写作及写作策略的学习和产出性质,最后文章提出了一个便于取舍同时也便于实证研究展开与操作的英语写作策略分类框架。     

汉字笔迹特征之分类

中国古代有关于汉字笔迹特征的论述,却没有系统的分类。汉字笔迹特征的分类有两大角度:笔迹鉴定的角度和笔迹心理分析的角度。文章阐述了汉字笔迹特征的分类情况,提出了力量特征、空间特征、关系特征和神韵特征的汉字笔迹特征的分类方法。     

康定市吉居藏语所属问题

本文针对分布在四川甘孜州康定市吉居乡的藏族语言进行分析。吉居话的语言所属在以往研究里没有共识,有属于扎巴语的意见和属于康巴藏语的意见。通过与藏文的对比,可见该语言为一个属于康巴藏语崩波岗方言群的土话,并非木雅语或扎巴语。基于与吉居话周边土话的比较,我们提出吉居话属于崩波岗方言群雅砻江组的假设性结论。本文的分析方法亦能作为识别康巴藏语中方言所属的参考。     

也谈历史行政地理分析法在方言分区中的应用——以苏沪嘉地区为例

利用《汉语方言地图集》的材料,对苏沪嘉地区方言的语音、词汇、语法进行综合比较.在此基础上,运用历史行政地理分析法,对苏沪嘉方言的分区方案进行讨论,指出维持原来划分的苏沪嘉小片是最佳方案.