再谈知识分子与人文精神

"五四"以来,尽管对"人文主义"(humanism)有不同的理解,但一般都认为人文主义的论述与知识分子是分不开的。知识分子是一种启蒙式的人文主义者,自古到今,在中国的社会文化领域里始终有着举足轻重的地位,特别是知识分子自己觉得他永远站在一个中心位置来影响社会。这个基本的立场,在20世纪70、80年代后开始受到挑战。随着知识的工业化、专业化或体系化,人文精神变得离我们越来越遥远,知识分子的社会承担也变得越来越无足轻重。对于传统的知识分子的身份定位问题,有必要重新解构,作出新的思考。知识分子应该从文化实践中产生出来,他可以在现代社会里扮演多个角色,通过这些角色营造对社会、对文化有影响力的论说空间,这种影响力不同于原来的社会承担,更多的是知识的推广。当代知识分子可能会向两个方向分化:一些人以专业知识为主,更加专业化;另一些人会成为文化型的行动知识分子。     

日本电影产业的经济学分析

运用一个国内市场的经济学模型,来阐释美日两国电影产业之间不断变化的竞争平衡关系,可以验证如下假设,即日本的国产电影市场份额减少是因为对美国电影消费的增长速度超过对日本本国电影的消费速度。根据美日媒体产业发展的数据资料（1955－2000）得出的结论支持了这一经济学假设。     

Interactive fuzzy goal programming for multi-objective transportation problems

This paper presents an interactive fuzzy goal programming approach to determine the preferred compromise solution for the multi-objective transportation problem. The proposed approach considers the imprecise nature of the input data by implementing the minimum operator and also assumes that each objective function has a fuzzy goal. The approach focuses on minimizing the worst upper bound to obtain an efficient solution which is close to the best lower bound of each objective function. The solution procedure controls the search direction via updating both the membership values and the aspiration levels. An important characteristic of the approach is that the decision maker's role is concentrated only in evaluating the efficient solution to limit the influences of his/her incomplete knowledge about the problem domain. In addition, the proposed approach can be applied to solve other multi-objective decision making problems. The performance of this solution approach is evaluated by comparing its results with that of the two existing methods in the literature.     

Social Worker Manpower,Community Economic Disadvantage,and Family Violence: Initial Evidence from Taiwan

This study is the first to explore the effect of social worker manpower on family violence incidents. In addition, it is the first study to investigate the geography of family violence in Taiwan. Using data from the County‐Level Important Indicator Query System, this study performs panel regressions to analyze the determinants of county‐level family violence incidents between 2005 and 2011. The empirical results clearly indicate that family violence incidents tend to be higher in counties that suffer economic disadvantage and in which there is an inadequate deployment of social worker manpower. The findings have important implications for combating family violence.     

Depth functions as measures of representativeness

Data depth provides a natural means to rank multivariate vectors with respect to an underlying multivariate distribution. Most existing depth functions emphasize a centre-outward ordering of data points, which may not provide a useful geometric representation of certain distributional features, such as multimodality, of concern to some statistical applications. Such inadequacy motivates us to develop a device for ranking data points according to their “representativeness” rather than “centrality” with respect to an underlying distribution of interest. Derived essentially from a choice of goodness-of-fit test statistic, our device calls for a new interpretation of “depth” more akin to the concept of density than location. It copes particularly well with multivariate data exhibiting multimodality. In addition to providing depth values for individual data points, depth functions derived from goodness-of-fit tests also extend naturally to provide depth values for subsets of data points, a concept new to the data-depth literature.     

Part‐Time Employment and Problem Behaviors: Evidence From Adolescents in South Korea

This study explores the impact of adolescent part‐time work experience on problem behaviors in the South Korean context. To achieve this, propensity score matching (PSM) analyses were employed based on data from the Korean Education Employment Panel (KEEP). Results indicate that adolescents' part‐time employment during their secondary school years had significantly undesirable effects on drinking and smoking, even after preexisting differences between the two groups (i.e., those adolescents who participated in part‐time work and those who did not) were controlled by PSM. However, an insignificant difference was detected in the likelihood of running away from home. Implications of the results are discussed in terms of changes in the meanings of adolescence and of participating in part‐time work in South Korea.     

Parameter change test for zero-inflated generalized Poisson autoregressive models

In this paper, we consider the problem of testing for parameter change in zero-inflated generalized Poisson (ZIGP) autoregressive models. We verify that the ZIGP process is stationary and ergodic and that the conditional maximum likelihood estimator (CMLE) is strongly consistent and asymptotically normal. Based on these results, we construct CMLE- and residual-based cumulative sum tests and show that their limiting null distributions are a function of independent Brownian bridges. The simulation results are provided for illustration. A real data analysis is performed on some crime data of Australia.     

Another look at linear programming for feature selection via methods of regularization

We consider statistical procedures for feature selection defined by a family of regularization problems with convex piecewise linear loss functions and penalties of l ₁ nature. Many known statistical procedures (e.g. quantile regression and support vector machines with l ₁-norm penalty) are subsumed under this category. Computationally, the regularization problems are linear programming (LP) problems indexed by a single parameter, which are known as ‘parametric cost LP’ or ‘parametric right-hand-side LP’ in the optimization theory. Exploiting the connection with the LP theory, we lay out general algorithms, namely, the simplex algorithm and its variant for generating regularized solution paths for the feature selection problems. The significance of such algorithms is that they allow a complete exploration of the model space along the paths and provide a broad view of persistent features in the data. The implications of the general path-finding algorithms are outlined for several statistical procedures, and they are illustrated with numerical examples.     

Exponentiated-exponential geometric regression model

A regression model, based on the exponentiated-exponential geometric distribution, is defined and studied. The regression model can be applied to count data with under-dispersion or over-dispersion. Some forms of its modifications to truncated or inflated data are mentioned. Some tests to discriminate between the regression model and its competitors are discussed. Real numerical data sets are used to illustrate the applications of the regression model.     

Resolving a Multi-Million Dollar Contract Dispute With a Latin Square

The City of New York negotiated a dispute over the performance of new garbage trucks purchased from a vehicle manufacturer. The dispute concerned the fulfillment of a specification in the purchase contract that the trucks load a minimum full-load of 12.5 tons of household refuse. On behalf of the City, but in cooperation with the manufacturer, the City's Department of Sanitation and consulting statisticians tested fulfillment of the contract specification, employing a Latin Square design for routing trucks. We present the classical analysis using a linear model and analysis of variance. We also show how fixed, mixed, and random effect models are useful in analyzing the results of the test. Finally, we take a Bayesian perspective to demonstrate how the information from the data overcomes the difference between the prior densities of the city and the manufacturer for the load capacities of the trucks to result in much closer posterior densities. This procedure might prove useful in similar negotiations. Supplementary material including the data and R code for computations in the article are available online.