西方政党政治中的利益集团、政党腐败及其治理

政党政治是西方民主政治的重要组成部分,是政治民主化的发展成果。政党的社会整合能力削弱,导致了西方政治过程中利益集团作为一支强大的力量强势崛起,并通过政治献金、游说向执政党施加压力,以期将集团的利益诉求通过执政党和政府的公共政策制定合法化。政党与利益集团的媾和促成了权力与利益的互换,政党腐败滋生,腐蚀和瓦解着当前政治体制,耗竭政党的社会基础与执政资源,威胁政党政治的生命。为此,只有完善政党与利益集团自身的组织规范,实现对政党权力的约束;改变单一的政党经费筹集方式,增强竞选经费使用的透明度;建立开放与多元竞争的公共政策制定机制,实现公共政策的利益均衡,构筑明确的权力与利益边界,才能重构政党与利益集团的关系,消减政党与利益集团的不正当交易,遏制腐败的发生。     

重庆土家族婚俗现状研究

重庆土家族婚俗文化,是巴渝文化的活化石。文章通过田野调查与相关文献研究,探讨土家族婚俗特色及其文化价值,试图为土家族婚俗(这一非物质文化遗产的保护工作)提供一些理性的思考。     

证券投资意识调查分析 —基于数据挖掘的视角

 证券公司对于客户的挖掘和分类有利于挖掘潜在客户和做出适当的营销决策。本文将决策树、逻辑斯蒂回归和贝氏机率分类算法用于判断被访者是否购买股票,以此挖掘潜在客户,用K-means聚类法将股票购买者划分不同的类型,并建议采取不同的服务和营销方式,提高客户的忠诚度。     

Ambiguous Criteria Weights in AHP: Consequences and Solutions*

Two related streams of criticism of the analytic hierarchy process (AHP) have not yet been satisfactorily resolved, although both date from the early 1980s. The first relates to ambiguity in the meaning of the relative importance of one criterion as compared to another. The second is concerned with reversals of rank alleged to be possible when new options are introduced in an AHP problem. Both proponents and critics of AHP agree that rank reversals occur, but disagree on the legitimacy of such reversals. This paper shows that there is a necessary correspondence between the manner in which criteria importances are interpreted and computed and the manner in which the weights of the options under each criterion are normalized. In general, if this relationship is ignored, incorrect weights are generated for options under consideration regardless of whether new options are added or deleted. A rank reversal on the addition of an option is merely symptomatic of this fact, and such reversals do not occur when the correspondence condition is met.     

Inference in a Binary Response Model with Applications to Data Analysis*

Standard errors of the coefficients of a logistic regression (a binary response model) based on the asymptotic formula are compared to those obtained from the bootstrap through Monte Carlo simulations. The computer intensive bootstrap method, a nonparametric alternative to the asymptotic estimate, overestimates the true value of the standard errors while the asymptotic formula underestimates it. However, for small samples the bootstrap estimates are substantially closer to the true value than their counterpart derived from the asymptotic formula. The methodology is discussed using two illustrative data sets. The first example deals with a logistic model explaining the log-odds of passing the ERA amendment by the 1982 deadline as a function of percent of women legislators and the percent vote for Reagan. In the second example, the probability that an ingot is ready to roll is modelled using heating time and soaking time as explanatory variables. The results agree with those obtained from the simulations. The value of the study to better decision making through accurate statistical inference is discussed.     

Data Driven Modeling: An Application in Scheduling

This paper presents a data driven modeling (DDM) approach to certain types of optimization problems. DDM relinquishes control of the completed model to the user department rather than the operations research (OR) staff. The approach emphasizes development of models that are dependent on data maintained and understood by the users. The data base consists of coded user rules which describe when changes will occur in the problem structure and data which captures the generalization of the problem. Both the rules and data can be updated by user department personnel. These data drive a matrix generator controlled by the rules which uses the data base as input to generate the specific model formulation. This DDM system is designed by OR consultants or staff to allow independence of use along with low-cost and minimal-effort maintenance. The DDM approach is illustrated with an application to a real-world medical scheduling problem.     

Determinants of in-group bias: Is group affiliation mediated by guilt-aversion?

In-group favoritism in social dilemma situations is one of Social Identity Theory’s main findings. We investigate what causes the in-group bias: is it merely due to group affiliation or, alternatively, is guilt-aversion moderating the strength of in-group favoring? We induce group membership in a minimal group setting, observe in-/out-group transfers and elicit corresponding beliefs. According to our experimental data group affiliation affects beliefs and explains a substantial part of the bias. Evidence for guilt-aversion is found only when beliefs are elicited before actions.     

A two phases queueing system with Bernoulli vacation schedule under multiple vacation policy

This paper deals with a single server Poisson arrival queue with two phases of heterogeneous service along with a Bernoulli schedule vacation model, where after two successive phases service the server either goes for a vacation with probability p (0≤p≤1) or may continue to serve the next unit, if any, with probability q(=1−p). Further the concept of multiple vacation policy is also introduced here. We obtained the queue size distributions at a departure epoch and at a random epoch, Laplace Stieltjes Transform of the waiting time distribution and busy period distribution along with some mean performance measures. Finally we discuss some statistical inference related issues.