Do single mothers in the United States use the Earned Income Tax Credit to reduce unsecured debt?

The Earned Income Tax Credit (EITC) is a refundable credit for low-income workers mainly targeted at families with children. This study uses the Survey of Income and Program Participation’s topical modules on Assets and Liabilities to examine associations between the EITC expansions during the early 1990s and the unsecured debt of the households of single mothers. We use two difference-in-differences comparisons over the study period 1988–1999, first comparing single mothers to single childless women, and then comparing single mothers with two or more children to single mothers with exactly one child. In both cases we find that the EITC expansions are associated with a relative decline in the unsecured debt of affected households of single mothers. While not direct evidence of a causal relationship, this is suggestive evidence that single mothers may have used part of their EITC to limit the growth of their unsecured debt during this period.     

The American Way

Media consolidation and convergence have increasingly changed the way individuals as both consumers and citizens access, process, and communicate information at the local, national, and global levels. Media industries and institutions influence public perception and occupy our time at work and at home more and more. Media literacy has become recognized as a twenty-first-century skill necessary for civic competence and the development of informed, responsible citizens. Although it has long been established in the curricula of other nations, it is relatively new in the United States. Media literacy is not simply teaching with media—rather, it entails teaching about media. Key frameworks such as the Text, Audience, and Production (TAP) model, which is explained in this article, can be used to help students systematically analyze and evaluate the wide range of media texts they are exposed to on a daily basis. The author discusses how media literacy is also compatible with several of the major strands identified by the National Council for the Social Studies and can be facilitated by the growing range of resources available to teachers.     

Transformation and Smoothing in Sample Survey Data

Abstract. We consider model‐based prediction of a finite population total when a monotone transformation of the survey variable makes it appropriate to assume additive, homoscedastic errors. As the transformation to achieve this does not necessarily simultaneously produce an easily parameterized mean function, we assume only that the mean is a smooth function of the auxiliary variable and estimate it non‐parametrically. The back transformation of predictions obtained on the transformed scale introduces bias which we remove using smearing. We obtain an asymptotic expansion for the prediction error which shows that prediction bias is asymptotically negligible and the prediction mean‐squared error (MSE) using a non‐parametric model remains in the same order as when a parametric model is adopted. The expansion also shows the effect of smearing on the prediction MSE and can be used to compute the asymptotic prediction MSE. We propose a model‐based bootstrap estimate of the prediction MSE. The predictor produces competitive results in terms of bias and prediction MSE in a simulation study, and performs well on a population constructed from an Australian farm survey.     

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.     

Methodology for the Calculation of Annualized Incremental Risks in Systems of Dams

In the past few years, the field of dam safety has approached risk informed methodologies throughout the world and several methodologies and programs are appearing to aid in the systematization of the calculations. The most common way of implementing these calculations is through the use of event trees, computing event probabilities, and incremental consequences. This methodology is flexible enough for several situations, but its generalization to the case of systems of several dams is complex and its implementation in a completely general calculation methodology presents some problems. Retaining the event tree framework, a new methodology is proposed to calculate incremental risks. The main advantage of this proposed methodology is the ease with which it can be applied to systems of several dams: with a single risk model that describes the complete system and with a single calculation the incremental risks of the system can be obtained, being able to allocate the risk of each dam and of each failure mode. The article shows how both methodologies are equivalent and also applies them to a case study.     

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.