Individual Participation in Collective Action in the Context of a Caribbean Island State: Testing the Effects of Multiple Dimensions of Social Capital

This article presents the findings of a case study examining the relationship between social capital and individual participation in collective action on a Caribbean island recovering from devastation inflicted by Hurricanes Ivan and Emily. Using data drawn from 114 residential surveys on the island of Carriacou, Grenada, over the summer of 2006, we empirically test social capital as a predictor of individual participation in both formal and informal civic events. In addition, we further the theoretical development of the concept of social capital by independently testing the relationships between its multiple dimensions, specifically social networks; interpersonal trust; and norms of reciprocity. We find that associational membership and age are the two strongest predictors, while interpersonal trust, gender, and marital status are also significant. Our path analysis reveals that there is not a significant direct effect between associational membership and interpersonal trust, suggesting that the two dimensions may have independent, yet complementary, influences. This study sheds light on factors influencing citizen participation in “civic” forms of collective action in a developing region of the world, while demonstrating the multidimensional nature of social capital.     

Cognitive and Affective Factors Which Influence Downtown Behaviors

Abstract

Data collected on perceptions of downtown Atlanta are used to explore the impact of cognitive and affective assessments of place on the frequency with which individuals go downtown for shopping, business or professional services, and for entertainment activities. Findings include: (1) social background variables generally exert only weak effects on cognitive and affective responses to downtown Atlanta; (2) affective identification with downtown exerts a positive, significant, and powerful effect on the frequency of using downtown for shopping and business activities; (3) non-Whites, city residents, and singles are more likely to go downtown for entertainment activities than Whites, suburbanites, and married respondents; and (4) images of downtown, affective identification, and positive assessments of downtown municipal services encourage participation in downtown entertainment activities. The analysis strongly suggests that behaviors are influenced by the meanings and evaluations people create for an area.     

Puerto rican drug users’ experiences of physical and sexual abuse: Comparisons based on sexual identities

This study integrates the results of quantitative and qualitative methods to elucidate the association between sexual identity and physical and sexual abuse among Puerto Rican drug users. A structured questionnaire was administered to 800 subjects in New York and 399 in Puerto Rico. A total of 93 subjects (7.9%) self‐identified as homosexual or bisexual. Gay males were significantly more likely than heterosexual males to report first occurrence of physical abuse by a family member in childhood. Both gay and bisexual males were more likely than their heterosexual counterparts to report first experiencing unwanted sex in childhood and intimate partner physical abuse later in life. Lesbians were more likely than female heterosexuals to report unwanted sex in childhood. Qualitative data were collected through in‐depth life histories with 21 subjects and suggest that gay and lesbian subjects perceive antihomosexual prejudice on the part of family members as one cause of childhood physical and sexual abuse.     

Linked Data: What Is It and What Can It Do?

Abstract

There has been a lot of talk, discussion (and even buzz) on the Internet and in the library world recently on the whole issue of linked data and what it may mean, accomplish, and even change in the Internet and library worlds. This article will attempt to clarify what linked data is, some of the issues surrounding it, and explore some possible implications.     

Detection of outliers in simple circular regression models using the mean circular error statistic

The investigation on the identification of outliers in linear regression models can be extended to those for circular regression case. In this paper, we propose a new numerical statistic called mean circular error to identify possible outliers in circular regression models by using a row deletion approach. Through intensive simulation studies, the cut-off points of the statistic are obtained and its power of performance investigated. It is found that the performance improves as the concentration parameter of circular residuals becomes larger or the sample size becomes smaller. As an illustration, the statistic is applied to a wind direction data set.     

On Non-parametric Estimation of the Survival Function with Competing Risks

The non-parametric maximum likelihood estimators (MLEs) are derived for survival functions associated with individual risks or system components in a reliability framework. Lifetimes are observed for systems that contain one or more of those components. Analogous to a competing risks model, the system is assumed to fail upon the first instance of any component failure; i.e. the system is configured in series. For any given risk or component type, the asymptotic distribution is shown to depend explicitly on the unknown survival function of the other risks, as well as the censoring distribution. Survival functions with increasing failure rate are investigated as a special case. The order restricted MLE is shown to be consistent under mild assumptions of the underlying component lifetime distributions.     

The Ecology of Suicide in an Australian Metropolis: The Case of Sydney

The ecological patterns of suicide in metropolitan Sydney are described and policy recommendations made. Some inferences about the association of urbanization with suicide are suggested.     

Maximum entropy sampling and optimal Bayesian experimental design

When Shannon entropy is used as a criterion in the optimal design of experiments, advantage can be taken of the classical identity representing the joint entropy of parameters and observations as the sum of the marginal entropy of the observations and the preposterior conditional entropy of the parameters. Following previous work in which this idea was used in spatial sampling, the method is applied to standard parameterized Bayesian optimal experimental design. Under suitable conditions, which include non-linear as well as linear regression models, it is shown in a few steps that maximizing the marginal entropy of the sample is equivalent to minimizing the preposterior entropy, the usual Bayesian criterion, thus avoiding the use of conditional distributions. It is shown using this marginal formulation that under normality assumptions every standard model which has a two-point prior distribution on the parameters gives an optimal design supported on a single point. Other results include a new asymptotic formula which applies as the error variance is large and bounds on support size.