A divergence of opinion: how those involved in child and family social work are responding to the challenges of the Internet and social media

This discussion paper suggests that there is possibly a divergence of opinion taking place within the field of child and family social work and that the stated positions are influencing how practitioners identify and deal with risks and opportunities afforded by the Internet and social media. The suggested divergence is examined and the conclusion drawn is that what is taking place mirrors the fact that the introduction of any new technology inevitably brings with it division and debate. In seeking to understand the reaction to digital technology, consideration is given to a series of wider social discourses on childhood and risk, which includes the controversial notion that the profession is a harbinger of moral panic and that the management of risk has been broadened from child protection to child safety. The discussion paper concludes by calling for child and family social work practitioners to have a balanced debate that needs to be informed not only by current research but also by an open and honest discussion about personal use and an acknowledgement that there will be difficult moral and ethical questions to work through.     

Application of a QMRA Framework to Inform Selection of Drinking Water Interventions in the Developing Context

The aim of this study was to develop a modified quantitative microbial risk assessment (QMRA) framework that could be applied as a decision support tool to choose between alternative drinking water interventions in the developing context. The impact of different household water treatment (HWT) interventions on the overall incidence of diarrheal disease and disability adjusted life years (DALYs) was estimated, without relying on source water pathogen concentration as the starting point for the analysis. A framework was developed and a software tool constructed and then implemented for an illustrative case study for Nepal based on published scientific data. Coagulation combined with free chlorine disinfection provided the greatest estimated health gains in the short term; however, when long‐term compliance was incorporated into the calculations, the preferred intervention was porous ceramic filtration. The model demonstrates how the QMRA framework can be used to integrate evidence from different studies to inform management decisions, and in particular to prioritize the next best intervention with respect to estimated reduction in diarrheal incidence. This study only considered HWT interventions; it is recognized that a systematic consideration of sanitation, recreation, and drinking water pathways is important for effective management of waterborne transmission of pathogens, and the approach could be expanded to consider the broader water‐related context.     

开放经济下OFDI对产业结构升级效应及传导路径

开放经济下对外直接投资(OFDI)已成为我国融入世界经济的主要途径,在优化产业结构、推进经济转型等方面扮演着重要角色。根据OFDI与产业结构升级及传导路径的互动机理分析,在对安徽省OFDI投资概况和产业结构现状进行分析的基础上,选取2003—2017年相关数据为样本构建VAR模型,运用ADF检验、脉冲响应函数等方法从产业结构总水平角度,实证分析得出短期内安徽省OFDI所能带来的产业结构升级效应并不显著的结论。进而从具体传导路径角度,采用主成分分析法,从10个变量中提取主成分构建VAR模型,运用脉冲响应等方法实证分析得出安徽省OFDI可通过贸易、省内投资、就业和技术路径来促进产业结构升级。为此,安徽省应扩大OFDI规模,提升OFDI质量和效益;增强企业竞争实力和科技创新能力,优化对外投资结构;发挥政府宏观调控和政策引导作用,加大对企业的扶持力度。     

Procedural (in)justice,emotions, and compliance

The procedural justice model has become widely recognized as a key crime prevention and reduction strategy, spurring its adoption across police agencies throughout the United States in an effort to address mounting concerns regarding police use of force. Recent critiques, however, have called attention to the need for greater examination of potential contributing factors that are underdeveloped in investigations of the procedural justice model, including the role of emotions. This article takes stock of interdisciplinary advancements to critically examine scholarly investigations exploring associations between procedural (in)justice, emotions, and compliance behaviors within the context of police-citizen interactions. In doing so, continued gaps are identified. Lastly, this article concludes by identifying future pathways and recommendations for the scholarly advancement of our understanding of emotions and their continued relevance to the procedural justice model.     

“（是）……的”类句式已然义的层次性分析——以“S（是）AV（O）的”句式为例

以学界广为关注的“S（是）AV（（））的”句式为例，重点分析“（是）……的”类句式在语境、词汇和句法三个层面所显示的不同已然义特征，并以此为基础对国内外关于已然义“（是）……的”类句式的相关研究进行简要的评价。     

Racial diversity in the suburbs: how race-neutral responses to demographic change perpetuate inequity in suburban school districts

Suburbs across the US are experiencing dramatic demographic shifts, yet there is little research available on how suburban school districts are dealing with these changes. In this article, we examine the discourses surrounding race and demographic change in three suburban school districts that have been undergoing rapid demographic changes and which contain demographically distinct areas within their district boundaries. Utilizing a critical discourse analysis (CDA) approach, we analyze how the policy context (federal and state) frames actors’ discourses and understandings of race, paying particular attention to the political and institutional factors affecting school policy. We illustrate how the discourse, in turn, is related to the actions (or inactions) taken by district and school leaders to respond to demographic change. We conclude the article by discussing policy implications and potential challenges districts may face in the future if efforts to purposively address racial changes continue to be avoided.     

A latent variable model for analyzing mixed longitudinal (k,l)-inflated count and ordinal responses

A random effects model for analyzing mixed longitudinal count and ordinal data is presented where the count response is inflated in two points (k and l) and an (k,l)-Inflated Power series distribution is used as its distribution. A full likelihood-based approach is used to obtain maximum likelihood estimates of parameters of the model. For data with non-ignorable missing values models with probit model for missing mechanism are used.The dependence between longitudinal sequences of responses and inflation parameters are investigated using a random effects approach. Also, to investigate the correlation between mixed ordinal and count responses of each individuals at each time, a shared random effect is used. In order to assess the performance of the model, a simulation study is performed for a case that the count response has (k,l)-Inflated Binomial distribution. Performance comparisons of count-ordinal random effect model, Zero-Inflated ordinal random effects model and (k,l)-Inflated ordinal random effects model are also given. The model is applied to a real social data set from the first two waves of the national longitudinal study of adolescent to adult health (Add Health study). In this data set, the joint responses are the number of days in a month that each individual smoked as the count response and the general health condition of each individual as the ordinal response. For the count response there is incidence of excess values of 0 and 30.     

Whither practice-near research in the modernization programme? Policy blunders in children's services

In this article, we lament the effects of practice-distant research and associated policy initiatives on contemporary children's services in England. In the last decade, as a result of high profile inquiries into non-accidental child deaths, statutory children's social care services in the UK have been subject to a wide-reaching ‘modernization’ programme. We studied decision-making in the high blame environment of local authority children's services. Our research sought to examine the relationship between performance management and the impact of anticipated blame within the decision-making practices of those providing, supervising and managing these services. We show that systems and technologies can be developed which both assist the users in their daily work and achieve desired organizational goals, but without an ethnographically informed, practice-near approach, unsafe work regimes and practices can ensue.     

To be or not to be valid in testing the significance of the slope in simple quantitative linear models with autocorrelated errors

In this article, the validity of procedures for testing the significance of the slope in quantitative linear models with one explanatory variable and first-order autoregressive [AR(1)] errors is analyzed in a Monte Carlo study conducted in the time domain. Two cases are considered for the regressor: fixed and trended versus random and AR(1). In addition to the classical t -test using the Ordinary Least Squares (OLS) estimator of the slope and its standard error, we consider seven t -tests with n-2\,\hbox{df} built on the Generalized Least Squares (GLS) estimator or an estimated GLS estimator, three variants of the classical t -test with different variances of the OLS estimator, two asymptotic tests built on the Maximum Likelihood (ML) estimator, the F -test for fixed effects based on the Restricted Maximum Likelihood (REML) estimator in the mixed-model approach, two t -tests with n - 2 df based on first differences (FD) and first-difference ratios (FDR), and four modified t -tests using various corrections of the number of degrees of freedom. The FDR t -test, the REML F -test and the modified t -test using Dutilleul's effective sample size are the most valid among the testing procedures that do not assume the complete knowledge of the covariance matrix of the errors. However, modified t -tests are not applicable and the FDR t -test suffers from a lack of power when the regressor is fixed and trended ( i.e. , FDR is the same as FD in this case when observations are equally spaced), whereas the REML algorithm fails to converge at small sample sizes. The classical t -test is valid when the regressor is fixed and trended and autocorrelation among errors is predominantly negative, and when the regressor is random and AR(1), like the errors, and autocorrelation is moderately negative or positive. We discuss the results graphically, in terms of the circularity condition defined in repeated measures ANOVA and of the effective sample size used in correlation analysis with autocorrelated sample data. An example with environmental data is presented.     

Bandwidth selection through cross-validation for semi-parametric varying-coefficient partially linear models

We study bandwidth selection for a class of semi-parametric models. The proper choice of optimal bandwidth minimizes the prediction errors of the model. We provide detailed derivation of our procedure and the corresponding computation algorithms. Our proposed method simplifies the computation of the cross-validation criteria and facilitates more complicated inference and analysis in practice. A data set from Wisconsin Diabetes Registry has been analysed as an illustration.