Racial classification in criminology: The reproduction of racialized crime

The (re)production of knowledge about crime is cultural in terms of the questions asked, the comparisons made, and the hypotheses selected to explain crime causation. Since criminologists do not operate in a vacuum, any prejudgments, biases, and beliefs acquired before their professional socialization may well persist and affect their approach to research over the course of their academic careers. Because American criminologists live in a society that racializes a number of problem behaviors, including crime, it is conceivable that widely held beliefs about race that predate graduate training will find their way into assumptions about the relationship between race and crime. Such preprofessional beliefs are transformed into facts when they meet with widespread agreement from other criminologists and thus come to be taken for granted in the objective pursuit of knowledge. Crime is racialized, for example, when the criminal behaviors of individual black offenders are understood in terms of racial traits, racial motives, or racial experiences. When traits, motives, or experiences are classified as the property of whole races or racial communities, these conceptions of race assume causal significance in explaining criminal behavior. Because these traits, motives, and experiences are supposedly shared by entire races or race-class categories, the predisposition to criminality becomes generalized beyond individual Black criminals to whole races or racial communities of noncriminal Blacks. When crime is thus racialized, whole communities or whole categories of phenotypically similar individuals are rendered precriminal and morally suspect. In addition, such racializations in academic criminology can be used to justify increased control of individual black criminals in the larger society; these controls can also legitimately be extended to encompass whole communities and whole categories of phenotypically similar persons who are not involved in crime. This paper will address the role that racializing assumptions play in traditional criminological theories.     

Modeling household fertility decisions with generalized Poisson regression

This paper models household fertility decisions by using a generalized Poisson regression model. Since the fertility data used in the paper exhibit under-dispersion, the generalized Poisson regression model has statistical advantages over both standard Poisson and negative binomial regression models, and is suitable for analysis of count data that exhibit either over-dispersion or under-dispersion. The model is estimated by the method of maximum likelihood. Approximate tests for the dispersion and goodness-of-fit measures for comparing alternative models are discussed. Based on observations from the Panel Study of Income Dynamics of 1989 interviewing year, the empirical results support the fertility hypothesis of Becker and Lewis (1973). Received January 7, 1997 /Accepted April 3, 1997     

基于ARTⅡ网络的煤炭资源资产分类研究

本文建立了用于煤炭资源资产分类的ARTⅡ神经网络模型,编制了相应的计算机和软件,并将ARTⅡ模型与模糊分类模型和基于BP网络的分类模型进行了对比分析,实例运行结果表明,用ARTⅡ网络进行分类具有分类稳定、结果可靠等特点。     

信息不完全确定的区域产品模糊区间聚类方法

区域产品分类与选择是区域经济发展中最重要和最基础的工作.在产品选择与分类时,需要确定指标权系数和分类阈值等参数,这在实际应用中是比较困难的.针对这种情况,提出了一种信息不完全确定的区域产品模糊区间聚类方法.该方法构建了指标权系数信息不完全确定的最优模糊区间聚类模型,利用遗传算法和改进的FCM算法联合求解所得优化模型,得到指标权系数、最优聚类中心和最优划分,进而确定各产品所属类别.最后将该方法应用于某区域的产品分类和主导产品的确定中,实例计算说明该方法的可行性和有效性.     

新旧世界葡萄酒质量表达演变及形成

葡萄酒等级是全球葡萄酒行业的关注点。在旧世界葡萄酒等级表达中,产品等级不仅反映产品内在质量,还与具有质量风格的地理特征紧密相关;新世界葡萄酒等级表达中,葡萄酒地理特征仅表示产品来源真实性,葡萄酒质量以产品口感为基础并满足消费者消费偏好需求。葡萄酒官方等级分级具有从产区到列级酒庄的纵向化结构,葡萄酒等级分类具有从品种、年份到酒庄的横向化结构,前者分级以生产者视角下“为何分级”并同时聚焦分级内生形成关键要素,后者分类以消费者视角下“为何分类”并锚定产品质量的某一关键要素,两者之间关注点存在差异。这种差异给国际葡萄酒市场创造竞争空间,形成一种质量表达的实践共创、智慧共存的竞争格局。     

苏赋十题

本文首为苏赋辨伪,认为《苏轼文集》所收苏赋27篇,有两篇非苏轼作品。次为苏赋编年,二至五题逐篇考订了苏赋的写作时间。再次为苏赋辨体,六至八题分别论述了苏轼的骚体赋、律赋和文赋,认为苏赋诸体皆备,苏轼以文赋闻名于赋史,但他的文赋并不多。九题论苏轼仍以骈赋为多,着重论苏赋分类,认为苏赋题材十分丰富,含议政、纪游、吊古、咏物,苏轼不善饮酒,而咏酒赋特多。十题是比较二苏赋之异同,苏辙现存赋仅9篇,远较苏轼为少,作《缸砚赋》时年仅17岁,比《赤壁赋》的写作时间早25年。其《服菔苓赋》在当时已传到契丹,其《黄楼赋》尤为有名,杨万里甚至把《黄楼赋》与前后《赤壁赋》相提并论。     

基于相似日聚类和贝叶斯神经网络的光伏发电功率预测研究

光伏发电功率的预测是光伏发电规划和运行的基础,因而受到越来越多的重视。文中提出了FCM相似日聚类与智能算法相结合的光伏阵列功率短期预测模型。该方法的思路是首先通过分析影响光伏阵列输出功率的主要因素,对历史数据与预测日气象环境进行模糊分类,并筛选出相似度高的子集作为样本,以提高预测样本的质量;然后通过神经网络映射出特征空间与光伏功率之间的复杂关系,并用贝叶斯理论对神经网络参数进行优化,提高网络的泛化能力。为检验该方法的有效性和精确性,将所提出方法与常用BP神经网络模型对同一仿真算例进行预测,预测结果表明本文提出的预测模型效果更佳。     

基于GCA-DEA-MSVC方法的高校科研平台评价预测研究

高校科研平台评价与预测分析是促进科研工作健康高效发展的重要载体,但数据指标繁冗、逻辑关系复杂、影响因素众多等大大加剧了科研平台运行评价和预测难度。本文从大数据角度出发探索一种基于GCA-DEA-MSVC方法的高校科研平台评价预测方法。首先利用GCA方法从科研平台运行数据库中挖掘、提取出与评价结果密切相关的关键特征指标并进行分类构建特征指标库,然后利用DEA方法对特征指标库数据进行融合,提升数据质量构建相对效率指标库;最后,将特征指标库与相对效率指标库再次融合,基于改进的MSVC方法构建了高效的科研平台运行状态评价分类预测模型,并利用教育部重点实验室评价数据开展了实验研究,验证了所提方法的有效性。     

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。