上市公司管理舞弊的治理——基于管理层报酬契约设计分析

管理舞弊作为管理层追求机会主义而实施的欺诈性行为,它与管理报酬契约的天然不完备性、业绩评价指标的缺陷性及管理报酬契约的隐性激励有很大关系。我国的管理报酬虽然连年大幅度增长,但一直存在着管理报酬结构单一、管理报酬与业绩相关性差、缺乏长期显性激励等缺陷,导致管理舞弊案件频繁发生。所以可以考虑完善在报酬契约中加入对高管实现公司长期发展目标的考核,并使考核结果能在当年年度报酬中得到反映这样一种隐性长期激励形式。     

人文素质类隐性课程开发研究

本文在人文素质类校本课程开发的框架下,回顾了一般意义上的隐性课程的涵义、分类和特点;指出了人文素质类校本课程中隐性课程的具体表现形式和作用;探讨了整合、利用、管理、评价人文素质类校本课程中的隐性课程的主要措施。     

哲学视域中的叶嘉莹词学

本文从哲学的视角对叶嘉莹词学思想中“弱德之美”、“词学困惑”与“双性特征”、“苏词之幽咽怨断”三个论题作出分析 ,试图指出这些论题不仅是词学所面对的问题 ,而且是关涉到哲学所面对的人生意义问题。从而看到叶嘉莹词学中包孕着对人生终极意义的深切关怀 ,超越了具体学科的限制。     

高校学生社团隐性育人功能刍议

高校学生社团最根本的出发点就是育人,它是学生自我教育、自我管理、自我服务和自我成长的有效载体,更是当前学校素质教育和校园文化建设的重要途径。在发挥高校学生社团常规育人功能的同时,进一步挖掘隐性育人功能,构建高校学生社团隐性育人体系,对促进高校学生社团的长远发展,培育社会化、高素质、有公民意识的复合型人才具有十分重要的意义。     

论贾仲名的三种恋情剧

明代杂剧作家贾仲名的作品,在当时以香艳华丽著称,然而被近现代的各种戏曲史、文学史认为关目曲辞均平凡。考虑到贾仲名杂剧的演出场所和御用文人的创作身份,不难理解在那些看来空洞的伦理掩饰下,杂剧是如何将男女的物欲、情欲或酣畅、或委婉地表达出来。仅以他的三种恋情剧为例,从性别的文化意义视角来解读贾仲名的这类剧作。     

数学隐蔽条件类型探析

数学隐蔽条件是解决数学问题的重要组成部分。数学问题一般所关联的内容较多 ,范围和跨度都较大 ,因此它的隐蔽条件也较多。正确地发掘、识别和使用数学隐蔽条件 ,是培养解决数学问题能力的基础     

‘Hidden identities’: perceptions of sexual identity in Beijing

This article draws upon responses given by volunteers who work in the Beijing LGBT Centre regarding perceptions of sexual identity, and how Chinese culture affects hidden or open sexual identities of Chinese lesbian and gay people in this region. The insights gained from those working carefully to create social change offers an important and original contribution to the field of gay and lesbian studies in China. The findings indicate the volunteers at the Beijing LGBT Centre are frustrated by the lack of acceptance of non‐heterosexual relationships among Chinese culture and society, and by the disregard of lesbian gay and bisexual (LGB) people by the Chinese government. The findings also illustrate stigmatization of homosexuality in China is enacted in structural terms (such as in the lack of policy, legislation and positive endorsement by governmental and socio‐political organizations), public expression (such as negative attitudes, beliefs or reactions towards LGB people) and internalized repression (through fear of stigmatization, and subsequent abuse due to negative societal attitudes and discrimination). Influenced by the Chinese tradition of conforming to group values, the findings from this study show that volunteers at the Beijing LGBT Centre believe LGB people in China are generally hesitant to disclose their sexual identities, and reject the idea that there had been a collective shift in Chinese culture regarding increased acceptance of LGB people. It also finds volunteers at the LGBT Centre in Beijing blame Chinese culture for its lack of acceptance of non‐heterosexual relationships, and state stigmatization of homosexuality in China is due to deep‐rooted cultural homophobia.     

Parallelizing particle filters with butterfly interactions

The bootstrap particle filter (BPF) is the cornerstone of many algorithms used for solving generally intractable inference problems with hidden Markov models. The long-term stability of the BPF arises from particle interactions that typically make parallel implementations of the BPF nontrivial. We propose a method whereby particle interaction is done in several stages. With the proposed method, full interaction can be accomplished even if we allow only pairwise communications between processing elements at each stage. We show that our method preserves the consistency and the long-term stability of the BPF, although our analysis suggests that the constraints on the stagewise interactions introduce errors leading to a lower convergence rate than standard Monte Carlo. The proposed method also suggests a new, more flexible, adaptive resampling scheme, which, according to our numerical experiments, is the method of choice, displaying a notable gain in efficiency in certain parallel computing scenarios.     

Semiparametric hidden Markov model with non-parametric regression

The hidden Markov model regression (HMMR) has been popularly used in many fields such as gene expression and activity recognition. However, the traditional HMMR requires the strong linearity assumption for the emission model. In this article, we propose a hidden Markov model with non-parametric regression (HMM-NR), where the mean and variance of emission model are unknown smooth functions. The new semiparametric model might greatly reduce the modeling bias and thus enhance the applicability of the traditional hidden Markov model regression. We propose an estimation procedure for the transition probability matrix and the non-parametric mean and variance functions by combining the ideas of the EM algorithm and the kernel regression. Simulation studies and a real data set application are used to demonstrate the effectiveness of the new estimation procedure.