“参与式财政”：国外地方治理的实践创新——以巴西阿雷格里市为参照

20世纪后期以来,“参与式财政”(Participatory Budgeting)的出现,是国外地方治理中公民个人和不同群体、不同利益的代表直接参与地方和社区公共财政的开支和投资决策的一种新的实践方式,其运作中的公开性、参与性、互动性和制度化等特点及其产生的积极成效,对我国农村基层民主发展具有重要的借鉴价值。     

On the integration of public law jurisprudence

After two to three hundred years of development, modern public laws have become more and more important, mature and integrated especially since the 20^th century. Traditionally, the dispersive and overlapping public law researches were grounded on the sectional public laws like constitutional law, administrative law, criminal law, procedural law, international public law, etc. Nevertheless, with all-around emergence of public law, the traditional research method can no longer adapt to the development needs of the modern public law. Therefore, it is quite necessary for us to create a kind of moderate unified public law between the laws and the sectional public laws, so as to do comprehensive, integrated and systematic researches on various sectional public laws. Based on the indepth argumentation about the necessity of developing unified public laws, this paper further puts forward that, to discuss an all-encompassing way about the main problems of creating the unified public laws and expect to fill the gap with it, the unified public law should define its study objectives mainly focused on the contents of integrated public law criteria, common public law features and general public law rules and so on; form its theoretical basis on the line of the relations between public power and the citizen privilege; establish its category structure found on the concept of public power and the derivative core and basic categories; and build up the disciplinary system based on the systematic integrity of the public law research results.     

能动司法语境下二倍工资的法律适用问题

二倍工资是劳动合同法创立的一项新制度,但法律规定并不完善,二倍工资的适用范围、计算基数、仲裁时效等基本问题还比较模糊,认识也不统一。从价值衡量角度看,二倍工资制度的设定在保护劳动者利益的同时加重了企业负担,加之利益诱发的道德风险等因素,应充分发挥司法能动性和司法的调控机制,甄别不同情形,限制二倍工资的适用,兼顾企业利益。     

论课程的综合化

高校课程综合化的哲学基础是系统整体论 ,其直接原因则是学科的分化。学科的分化 ,深化了人类对自然界具体领域的认识 ,但同时它反映到高等学校的课程里 ,导致了科目增多 ,课程与社会要求的分离和课程与学习者的分离。这种弊端呼唤新的课程理念的建立 ,而课程综合化则应运而生     

国有控股企业职工董事问题刍议

建立职工董事、监事制度被认为是完善公司治理结构的有效方法 ,但在理论上还存在一些逻辑上的问题 ,在实践中也存在许多操作上的问题 ,主要是各利益主体之间的矛盾及外部环境与条件的限制。因此 ,解决这些问题最为有效的途径即建立职工持股制度。     

刑事鉴定结论研究

本文首先对鉴定结论得以存在的理论基础进行了剖析,指出鉴定结论的作用在于补充事实裁判者在专门问题上认识能力的不足;鉴定结论是一种证据,而非最终结论;鉴定结论作为一种独立的证据形式,是职权主义诉讼模式的产物.然后对鉴定的提出、鉴定人的选任以及对当事人双方的平等对待等问题进行了分析,在介绍了这一问题上的三种不同模式之后,指出了我国目前存在的问题及解决方式.之后又对鉴定人的主要权利和义务进行了评析.最后从证据能力和证明力两个方面讨论了鉴定结论的效力.     

情绪与自尊视角下的高校中青年教师职业倦怠研究

为了解高校中青年教师的职业倦怠现状,探讨情绪和自尊对职业倦怠的中介作用机制,本研究采用积极、消极情绪检核表、自尊量表和职业倦怠问卷,对北京市某高校175名中青年教师实施调查.结果发现(1)工作年限越长的教师情绪更枯竭、去人性化水平更高,成就感水平差异不显著;(2)积极情绪和自尊显著负向预测职业倦怠,消极情绪显著正向预测职业倦怠;(3)自尊部分中介积极情绪对情绪枯竭和低成就感的影响,部分中介消极情绪对情绪枯竭和去人性化的影响,完全中介积极情绪对去人性化的影响和消极情绪对低成就感的影响.研究结果验证了积极、消极情绪双变量模型,与情绪相比,自尊对职业倦怠的影响更直接,这为改善职业倦怠提供了有价值的参考.     

浅析中印气候变化合作

在全球环境变化日趋严峻的今天，气候变化问题已经成为世界政治中最具挑战性的议题之一，世界各国合作应对气候变化的挑战成为必然的选择。中印两国由于在气候变化政策方面原则和立场接近而开始进行气候变化合作。中印两国就气候变化问题进行合作，既有助于推动国际气候变化谈判取得实质性成果，也有助于双边关系的长远发展和新的国际治理与全球权力中心的形成。     

液质联用仪自动筛选常见安眠镇静药的应用研究

目的建立快速、灵敏的常见安眠镇静药物的液质联用仪的定性筛选方法。方法采用ZORBAX sb-aq,150mm×2.1mm×3.5μm(带预柱)色谱柱;柱温:30℃;流动相:甲酸(0.1%)甲醇和甲酸(0.1%)水溶液梯度条件;流速:0.4mL/min;通过电喷雾电离,自动三级扫描质谱。结果通过软件自动处理数据,建立了57种常见安眠镇静药的质谱谱库和保留时间参数谱库。结论建立的常见安眠药谱库和分析方法具有快速、灵敏、准确的优点,不易造成漏检,并且用于实际案件检验。     

A Comparison of Logistic Regression,Classification and Regression Tree,and Neural Networks Models in Predicting Violent Re-Offending

Previous studies that have compared logistic regression (LR), classification and regression tree (CART), and neural networks (NNs) models for their predictive validity have shown inconsistent results in demonstrating superiority of any one model. The three models were tested in a prospective sample of 1225 UK male prisoners followed up for a mean of 3.31 years after release. Items in a widely-used risk assessment instrument (the Historical, Clinical, Risk Management-20, or HCR-20) were used as predictors and violent reconvictions as outcome. Multi-validation procedure was used to reduce sampling error in reporting the predictive accuracy. The low base rate was controlled by using different measures in the three models to minimize prediction error and achieve a more balanced classification. Overall accuracy of the three models varied between 0.59 and 0.67, with an overall AUC range of 0.65–0.72. Although the performance of NNs was slightly better than that of LR and CART models, it did not demonstrate a significant improvement.