Issues in Implementing a Comprehensive Intervention for Public School Children With Autism Spectrum Disorders

Many students with autism spectrum disorders (ASD) are educated separately from their typically developing peers, while others are placed in inclusive classes but without supports that would help them benefit from less restrictive placements. The needs of students with ASD who are in inclusive settings are often not planned for or met appropriately, resulting in continuing problems and movement to increasingly restrictive environments or private placements. There is a critical need for school models to fill the gap in appropriate services for this population of children with ASD. These models should include those that are inclusive and academically challenging, that can be implemented by many school districts, and that are responsive to the unique combination of strengths and deficits in these students. In the current article, the authors describe the development and core components of the model, and implementation of the ASD Nest program in public schools in New York City.     

Reconsidering the Relationship Between Welfare Spending and Serious Crime: A Panel Data Analysis with Implications for Social Support Theory

Several researchers have found an inverse relationship between welfare spending and serious crime. With few exceptions, these findings have been based on cross‐sectional designs, single measures of welfare spending, and few indicators of crime. In response to these limitations, the relationship between welfare spending and crime was reconsidered using panel data from California counties. Fixed‐effects regressions revealed virtually no relationship between several measures of welfare spending and five types of serious crime: (1) homicide; (2) robbery; (3) assault; (4) burglary; and (5) larceny. The estimates were resistant to numerous robustness checks and alternative specifications. The most plausible explanation for the findings is that heterogeneity was not controlled for in previous studies. Implications for social support theory are discussed.     

中国工业经济绩效的实证研究——基于36个行业的面板数据

该文利用1993-2008年的36个工业行业的面板数据,通过固定效应模型,实证研究了工业行业的经济绩效与影响因素之间的关系。研究结果表明,提高工业行业的经济绩效关键在于行业效率和市场需求。从分行业的角度看,影响行业绩效的因素与生产型行业和消费型行业的行业特征有关。根据该文的研究表明,对于某些行业,试图通过兼并或重组等方式扩大行业规模、提高行业产值和行业集中度的做法来提高行业绩效,有可能适得其反。     

社会网络的动态过程及理论探索

本论文关注社会网络研究经常被忽视的一个层面,即社会网络的动态过程。在对相关理论的批判性回顾基础上,提出了一个整合结构、文化与个人能动性的理论框架以全面洞察个人的社会网络在社会文化脉络下的动态变化。     

WTO争端解决机制专家组程序问题评析

DSU专家组程序是WTO在争端解决机制中创设非常成功的解决国际经济争议的一项制度,在很多方面对传统国际中争议解决作了发展,也取得了相对令人满意的效果。运行10年来逐渐暴露出一些自身的缺陷,尤其反映在专家组组成方面,专家组成员的选拔与工作负担问题;中期评审制度;专家组报告和上诉机构报告的效力等方面,文章拟分析这些问题存在的原因,对争端解决机制的完善与公正运作提出一些建议。     

Estimation of arrest careers using hierarchical stochastic models

This paper introduces a general procedure using hierarchical stochastic models for characterizing criminal careers within a population of heterogeneous offenders. Individuals engage in criminal careers which are treated as stochastic processes governed by fixed parameters (e.g., a rate parameter), and these parameters come from specified distributions. The parameters of these distributions at the upper level of the hierarchy must then be specified. The models are estimated using data on all persons arrested at least once in the six-county Detroit Standard Metropolitan Statistical Area during the 4 years 1974–1977 for a criterion offense (an index crime other than larceny) and arrested at least once for robbery through April 1979. The collected data set is not a random sample of all such offenders in the population. There is a bias toward selecting those with a higher arrest frequency. In order to make more general inferences, statistical adjustment was needed to overcome the arrest-frequency sampling bias. We construct a series of models for the arrest career and fit the models with the data set of arrests. After correcting biases in the data, we estimate the model parameters using empirical Bayes methods and then examine the resulting models.     

Developmental explanations of delinquent behavior among siblings: Common factor vs. transmission mechanisms

We compare the statistical fit of two developmental explanations of delinquent behavior using longitudinal sibling data. The transmission effects model relates future delinquency to prior delinquency, delayed sibling effects, and unique environment. The common-factor effects model adds to these influences a latent variable representing persistent causes shared by siblings. These two models were fit to longitudinal data on 470 sibling pairs interviewed on three occasions. The common-factor effects model fit the data more closely than the transmission model. Nonmutually exclusive interpretations of the common effects model include (a) personality dispositions and (b) unchanging aspects of the social environment such as concurrent sibling effects and siblings' common friends.     

Growth curves of deviant behavior in early adolescence: A multilevel analysis

Multilevel growth curve models provide a means of analyzing individual differences in the growth of deviance, allow a number of theories to be integrated in a single model, and can help to unify research on deviant/delinquent/criminal careers at different stages of the life cycle. Building on the distinction between population heterogeneity and state dependence as alternative explanations of persistent individual differences in deviance (Heckman, 1981; Nagin and Paternoster, 1991), we show that models with two levels can be used to represent and analyze a variety of criminological theories. The first level (level 1) uses repeated measurements on individuals to estimate individual-level growth curves. The second level treats the level 1 growth curve parameters (e.g., slope, intercept) as outcome variables and uses time-invariant factors to explain variation in these parameters across individuals. We illustrate this approach by estimating a model of growth in deviance drawn from Gottfredson and Hirschi's deviant propensity theory. An innovative feature is the assumption that adolescents' expected growth curves of deviance follow a classical Pearl-Verhulst logistic growth model (Pearl, 1930). The results suggest that five risk factors—parental psychiatric problems, lack of parental support, living arrangements with zero or one parent in residence, low family income, and male gender—have strongly positive effects on deviant propensity. For example, adolescents with no supportive parents, and no other risk factors, have expected asymptotic levels of deviance (peak levels attained at about age 18) that are about twice as high as those of adolescents with no risk factors. Yet more than two-thirds of the individual-level variability in growth curves is unexplained by the five risk factors. This unobserved heterogeneity would remain hidden in analyses using conventional structural equations models and the same explanatory variables.