What does self-esteem have to do with behavioral health among low-income youth in Chicago?

Many studies have examined risk factors associated with poorer behavioral health among low-income African American youth, such as low school engagement, delinquency, mental health problems, drug use, and risky sex. However, fewer studies have examined protective factors for such behavioral health risk behaviors. This study sought to address this gap by examining whether high levels of self-esteem were associated with better behavioral health factors for this population. A survey was administered to a sample of 638 low-income African American adolescents in Chicago to examine the degree to which high self-esteem was associated with less delinquency, substance use, and sexual risk behaviors, and more school engagement, and whether such associations varied by gender. Stepwise linear and logistic regression models were estimated to assess the influence of self-esteem. Higher self-esteem for this sample of low-income African American adolescents was associated with lower rates of delinquency, drug use, and risky sexual behaviors and increased rates of school engagement. Gender moderated only a few of these relationships. These findings suggest that programs that promote high self–esteem alone or in combination with other resilience factors may promote better behavioral health factors for African American adolescents.     

Flood risk mapping and analysis using an integrated framework of machine learning models and analytic hierarchy process

In this study, a new approach of machine learning (ML) models integrated with the analytic hierarchy process (AHP) method was proposed to develop a holistic flood risk assessment map. Flood susceptibility maps were created using ML techniques. AHP was utilized to combine flood vulnerability and exposure criteria. We selected Quang Binh province of Vietnam as a case study and collected available data, including 696 flooding locations of historical flooding events in 2007, 2010, 2016, and 2020; and flood influencing factors of elevation, slope, curvature, flow direction, flow accumulation, distance from river, river density, land cover, geology, and rainfall. These data were used to construct training and testing datasets. The susceptibility models were validated and compared using statistical techniques. An integrated flood risk assessment framework was proposed to incorporate flood hazard (flood susceptibility), flood exposure (distance from river, land use, population density, and rainfall), and flood vulnerability (poverty rate, number of freshwater stations, road density, number of schools, and healthcare facilities). Model validation suggested that deep learning has the best performance of AUC = 0.984 compared with other ensemble models of MultiBoostAB Ensemble (0.958), Random SubSpace Ensemble (0.962), and credal decision tree (AUC = 0.918). The final flood risk map shows 5075 ha (0.63%) in extremely high risk, 47,955 ha (5.95%) in high-risk, 40,460 ha (5.02%) in medium risk, 431,908 ha (53.55%) in low risk areas, and 281,127 ha (34.86%) in very low risk. The present study highlights that the integration of ML models and AHP is a promising framework for mapping flood risks in flood-prone areas.     

A Latent Class Analysis of Factors Associated with Levels of Aggression among Low-Income African American Youth in Chicago

Abstract

African American youth are often stereotyped as being more aggressive than and experience more severe negative social sanctions relative to their European American peers. This cross-sectional study assessed self-reported levels of aggression among a sample of 538 low-income African American youth in Chicago, and employed latent class analysis to determine groups of aggression. Major study findings showed low, middle high aggression group. The largest number of youth fell within the low aggression group. Social factors (e.g., low student-teacher connectedness, high risky peer norms, neighborhood violence, and family conflict) were associated with inclusion in the high aggression group. Intrapersonal factors (e.g., depression, anxiety, post-traumatic stress disorder) were associated with inclusion in the middle aggression group. Future longitudinal research should examine what factors are associated with movement across aggression groups and capitalize upon knowledge gained in the current study to develop interventions.     

Social housing estates and sustainable community development in South Korea

The purpose of this paper is to examine the characteristics and problems of social housing estates in South Korea, and to explore sustainable community development issues. In order to examine the social housing situation, a survey of the three social housing communities in Seoul was conducted. The survey evidence demonstrates that there is a growing stigma against the poor and social exclusion. This kind of social bias is likely to escalate the construction of social housing estates, which the poor concentrates in. Residents recognized that mixing public and private housing would be an issue and problematic. Public housing was thought to have a negative impact on the neighborhood. It is important to examine why these kinds of social problems arise. Applying the concept of social sustainability to low-income communities in urban Korea requires mobilizing residents and their governments to strengthen all forms of community capital.     

Factors Holding Back Small Third Sector Organizations’ Engagement with the Local Public Sector

In many developed countries there has been a shift from grants to contracts as a source of local public sector funding of the third sector. Smaller third sector organizations may struggle to compete for this funding due to the complex process of accessing and maintaining this funding and conveying their capabilities to funding providers. This study utilizes data from the United Kingdom to determine what factors increase these administrative and communication barriers for smaller organizations. Resources in income and volunteers affect perceptions of the process of obtaining funding. A solution may be standardization of evaluation and monitoring, but this may lead to isomorphism and loss of variety of provision. Better two‐way communication may allow local authorities to retain variety in public service provision through improved knowledge of their partners.     

Optimal designs of multivariate synthetic |S| control chart based on median run length

The multivariate synthetic generalized sample variance |S| (synthetic |S|) chart is a combination of the |S| sub-chart and the conforming run length sub-chart. A procedure for optimal designs of the synthetic |S| chart, based on the median run length (MRL), for both zero and steady-state modes are provided by minimizing the out-of-control MRL. The comparative results show that the synthetic |S| chart performs better than the standard |S| chart for detecting shifts in the covariance matrix of a multivariate normally distributed process, in terms of the MRL. An example is given to illustrate the operation of the synthetic |S| chart.     

A 25-year perspective on levels of analysis in leadership research

The purpose of this article is to present a comprehensive 25-year review of the incorporation of levels of analysis into conceptual and empirical leadership research published within Leadership Quarterly throughout its history. We assessed the population of Leadership Quarterly's research (790 research articles) on four key levels of analysis-based issues: (1) explicit statement of the focal level(s) of analysis; (2) appropriate measurement given level of constructs; (3) use of a multi-level data analysis technique; and, (4) alignment of theory and data. Prior reviews regarding levels of analysis incorporation into leadership research have been limited to major research domains. Results revealed that while both conceptual and empirical articles only explicitly state the focal level of analysis in approximately one-third of the articles, appropriate levels-based measurement and alignment between theory and data are relatively strong areas of achievement for the articles within Leadership Quarterly. Multi-level data analysis techniques are used in less than one-fifth of all articles. Although there is room for improvement, there is evidence that Leadership Quarterly is a premier outlet for levels-based leadership research. Given the increasing complexity of organizational science with regard to groups, teams and collectives, Leadership Quarterly has an opportunity to model for organizational research on how to build and test complicated multi-level theories and models.     

交际视野下的规约性隐含逻辑初探——以兼为因果关系词句为例

在翻译实践过程中往往会遇到某些规约性隐含逻辑现象。在这一过程中,译者往往需要通过相关的信息解码来重新建构语言。交际视野下的规约性隐含逻辑现象主要表现为三个方面,即三种典型的逻辑交际模式。对于原语与目的语之间的兼为因果关系词句应采取必要而灵活的方法和策略。     

罗素对周作人“非宗教”思想的影响

在周作人早期思想研究中,罗素的影响一直未能引起人们的注意。本文详细地考察了罗素的"非宗教"观、自由教育思想以及闲适观对周作人的影响。"五四"时期周作人对现代知识分子非理性宗教情绪的批判、对形形色色宗教的或准宗教的意识形态的警惕、以及对自由闲适生活的重视等均与罗素的影响密切相关,深入地探讨这些问题不仅有助于我们更准确地把握周作人的思想,而且有助于我们全面评价和研究他后来的蜕变及思想的复杂性。     

Children’s Resilience-Related Beliefs as a Predictor of Positive Child Development in the Face of Adversities: Implications for Interventions to Enhance Children’s Quality of Life

This paper reports the findings of a longitudinal childhood resilience study which investigated the relationship between resilience-related beliefs and positive child development. Three waves of data collection (T1, T2, and T3) were completed in January 2005, July 2005, and January 2006 with a sample of 843 grade 4 pupils, drawn from six primary schools in Hong Kong, and their parents or guardians. At T1, parents/guardians responded to a 24-item inventory of life adversities affecting their children since birth; at T1 and T3, they completed a 25-item Parental Assessment of Child’s Habit, which provided parental evaluation of children’s performance at home and in school. At T1, T2, and T3, children responded to a 58-item Child and Youth Resilience Measure, a 9-item scale on Chinese cultural beliefs about adversity, and an 11-item Chinese Resilience Measure for Children and Adolescents in Hong Kong. Regression analyses, based on linear mixed models, controlling for gender, T1 and T2 scores, personal variables, and random effects of schools, were conducted to test and validate the hypothesis that children’s resilience beliefs are predictive of positive child development, and that this predictive relationship is stronger with increasing adversity in children’s lives. Implications of these findings for the development of resilience-based interventions to enhance the quality of life of children facing adversities are examined.