The relationship between exposure to community violence and psychological distress among adolescents: a meta-analysis

This article is concerned with the "size of the relationship" between exposure to chronic community violence and psychological symptoms among adolescents. It analyzes all relevant empirical studies in the published literature during the last 20 years; uses quantitative methods to summarize findings; and estimates the effect size using meta-analysis. The 37 independent samples (n = 17,322) were coded on 19 categories, including size and characteristics of sample, and characteristics of the independent and dependent variables. Findings indicate that there is a positive correlation between exposure to community violence and psychological distress; and that the effect size (r = .25) of this relationship is low-medium. The estimated effect size of the relationship points to new issues such as the characteristics of the psychosocial dynamics of resilience in the face of exposure to community violence and how exposure to community violence interacts with other potentially traumatic experiences in the producing of psychological distress.     

Anglo Voting on Nativist Ballot Initiatives: The Partisan Impact of Spatial Proximity to the U.S.‐Mexico Border*

Objective. In this study, we examine how contextual factors influence voting behavior on nativist ballot initiatives using California's Propositions 187 and 227. We argue that spatial proximity to the border is associated with voting behavior on nativist initiatives. Methods. To examine the influence of environmental factors on Anglo voting behavior on nativist ballot initiatives, we utilize California Field Polls, U.S. Census data, and spatially referenced data generated using GIS software. Results. The results indicate that spatial proximity to the border is an important component in individual‐level voting on nativist initiatives and that the impact of proximity to the border on the vote for Propositions 187 and 227 varies as a function of individual‐level partisan affiliation. Conclusions. These findings hold implications for future research regarding the influence of geospatial boundaries and political behavior.     

SOCIAL ENTREPRENEURSHIP — FALSE PREMISES AND DANGEROUS FOREBODINGS

As a reaction against neo‐liberalism, Social Entrepreneurship has been promoted as the solution to welfare problems brought about by social change and persistent unemployment. The Social Entrepreneurship Movement (SEM) proposes the reconstruction of welfare by building social partnerships between the public, social and business sectors. Major aspects of this agenda include non‐profit organisations undertaking entrepreneurial ventures and the pooling of government welfare funding under the control of local communities. In this paper we argue that the SEM literature is based on two false premises: the failure to understand the true causes of mass unemployment, and the assumption that the government faces financial constraints in the provision of welfare services. We also argue that implementation of the SEM proposals would erode the rights‐based eligibility to universal welfare services based on the principle of social justice. We also conclude that the SEM is indistinguishable from neo‐liberalism and as such does not represent a viable solution to unemployment and the welfare needs that accompany it.     

The FACES Project: an academic-community partnership to improve end-of-life care for families

This article reports on a research partnership between a community-based hospice and a graduate school of social work. The purpose of the collaboration was to design and test a tool for assessing caregiver strain and resources in families caring for older adults receiving hospice home care services. Eighteen hospice home care social workers interviewed 162 caregivers for the study and provided their own assessment of the tool's clinical utility. Both strengths and challenges of the collaboration are evaluated and implications are discussed for social work practice and research, particularly academic-community research partnerships.     

Estimates of air pollution mitigation with green plants and green roofs using the UFORE model

The purpose of this study was to investigate the effect of green roofs and green walls on air pollution in urban Toronto. The research looked at the synergistic effects on air pollution mitigation of different combinations of vegetation by manipulating quantities of trees, shrubs, green roofs and green walls in the study area. The effects of these manipulations were simulated with the Urban Forest Effects (UFORE) model developed by the USDA Forest Service Northeastern Regional Station. While UFORE contains several modules, Module—D quantifies the levels of air pollution for contaminants such as NO₂, S0₂, CO, PM₁₀ and ozone as well as hourly pollution removal rates and the economic value of pollutant removal. Six vegetation scenarios were developed within the Toronto study area to compare different subsets of vegetation and their effect on air contaminants. Results of the study indicate that grass on roofs (extensive green roofs) could augment the effect of trees and shrubs in air pollution mitigation, placing shrubs on a roof (intensive green roofs) would have a more significant impact. By extension, a 10–20% increase in the surface area for green roofs on downtown buildings would contribute significantly to the social, financial and environmental health of all citizens.

Nonparametric inference and uniqueness for periodically observed progressive disease models

In many studies examining the progression of HIV and other chronic diseases, subjects are periodically monitored to assess their progression through disease states. This gives rise to a specific type of panel data which have been termed “chain-of-events data”; e.g. data that result from periodic observation of a progressive disease process whose states occur in a prescribed order and where state transitions are not observable. Using a discrete time semi-Markov model, we develop an algorithm for nonparametric estimation of the distribution functions of sojourn times in a J state progressive disease model. Issues of uniqueness for chain-of-events data are not well-understood. Thus, a main goal of this paper is to determine the uniqueness of the nonparametric estimators of the distribution functions of sojourn times within states. We develop sufficient conditions for uniqueness of the nonparametric maximum likelihood estimator, including situations where some but not all of its components are unique. We illustrate the methods with three examples.