Food for Thought: Analyzing Public Opinion on the Supplemental Nutrition Assistance Program

ABSTRACT

This project explores public opinion on the Supplemental Nutrition Assistance Program (SNAP) in news and social media outlets, and tracks elected representatives’ voting records on issues relating to SNAP and food insecurity. We used machine learning, sentiment analysis, and text mining to analyze national and state level coverage of SNAP in order to gauge perceptions of the program over time across these outlets. Results indicate that the majority of news coverage has negative sentiment, more partisan news outlets have more extreme sentiment, and that clustering of negative reporting on SNAP occurs in the Midwest. Our final results and tools will be displayed in an online application that the ACFB Advocacy team can use to inform their communication to relevant stakeholders.     

Are Disinhibited Social Behaviors Among Internationally Adopted Children Mediated by the Attachment Environment or by Children's Difficulties with Inhibitory Control?

Internationally adopted children show higher rates of disinhibited social behavior (DSB). Two competing explanations for DSB include difficulties in attachment specifically and deficits in inhibitory control more generally. This four-wave longitudinal study (a) documented the persistence of DSB among internationally adopted children and (b) tested the relative contributions of attachment environment versus inhibitory control difficulties in the persistence of DSB. Improvement in DSB was found 3 to 4 years post-adoption for the sample as a whole, although heterogeneity within the sample was present. Results from structural equation modeling and another test of mediation both indicated that the association between early deprivation and DSB was mediated by general difficulties with inhibitory control, not by attachment environment.     

Robust wavelet shrinkage using robust selection of thresholds

This paper considers the problem of selecting a robust threshold of wavelet shrinkage. Previous approaches reported in literature to handle the presence of outliers mainly focus on developing a robust procedure for a given threshold; this is related to solving a nontrivial optimization problem. The drawback of this approach is that the selection of a robust threshold, which is crucial for the resulting fit is ignored. This paper points out that the best fit can be achieved by a robust wavelet shrinkage with a robust threshold. We propose data-driven selection methods for a robust threshold. These approaches are based on a coupling of classical wavelet thresholding rules with pseudo data. The concept of pseudo data has influenced the implementation of the proposed methods, and provides a fast and efficient algorithm. Results from a simulation study and a real example demonstrate the promising empirical properties of the proposed approaches.     

An Exploration of the Influence of Household Poverty Spells on Mortality Risk

Household poverty is dynamic and characterized in terms of spells. Exposure to poverty accumulates through the recurrence and persistence of spells, leading to divergent family adaptive strategies that contribute to mortality risk. The data set used in this study is longitudinal and contains socioeconomic and demographic data of a nationally representative sample. The findings are (a) poverty significantly increases mortality risk, controlling for age, gender, and race; (b) the first spell is especially potent, and mortality risk declines rapidly during subsequent spells; and (c) both direction and strength of these estimates are robust to marital status, but power diminishes significantly net of education and employment.     

Correlates of Male Adolescents Carrying Handguns Among Their Peers

Data from the National Longitudinal Survey of Youth 1997 were used to examine factors associated with carrying a handgun among adolescent males. We expected that carrying a handgun would be associated with characteristics of the individual and with aspects of the contexts that are important for adolescents, such as the family, the peer group, the school setting, and the neighborhood. Consistent with these expectations, we found that adolescent males were more likely than their peers to carry handguns if they engaged in other problematic behaviors, had witnessed someone else being shot or shot at, and were involved in gangs. Boys under the age of 15 were less likely to carry a handgun if they were closely monitored by their mothers and respected their mothers, and they were more likely to carry a handgun if they frequently heard gunshots in their neighborhood or had a relative or friend who was a gang member. Males who were 15 and older were more likely to carry a handgun if they associated with peers who engaged in problematic behaviors.     

“Racist Propaganda”: discursive Negotiations on YouTube of Perceived Anti-White Racism in South Korea

This article analyzes YouTube comments about a Munhwa Broadcasting Company report that White “expatriates” in South Korea called xenophobic and racist. The research is important because there is a paucity of scholarship on White discourse outside the West and because there is limited work on YouTube as a space to articulate and negotiate discourses about racism. This is despite the increasingly complex flows of people and discourse around the globe. In this article, I argue that YouTube acted as a site of ideological negotiation in which Orientalist discourses were advanced under the cover of color-blind racism. Many of the YouTube comments framed Korea as xenophobic and racist, and even for self-identified White commenters sympathetic to the report, they did not challenge the construction of Korea as racist or the normative belief in postracism.     

Bayesian inference and model selection in latent class logit models with parameter constraints: an application to market segmentation

Latent class models have recently drawn considerable attention among many researchers and practitioners as a class of useful tools for capturing heterogeneity across different segments in a target market or population. In this paper, we consider a latent class logit model with parameter constraints and deal with two important issues in the latent class models--parameter estimation and selection of an appropriate number of classes--within a Bayesian framework. A simple Gibbs sampling algorithm is proposed for sample generation from the posterior distribution of unknown parameters. Using the Gibbs output, we propose a method for determining an appropriate number of the latent classes. A real-world marketing example as an application for market segmentation is provided to illustrate the proposed method.     

The Role of Heritage Language Development in the Ethnic Identity and Family Relationships of Adolescents from Immigrant Backgrounds

The influence of immigrant-background adolescents' heritage language (HL) proficiency and use of the language on parent–adolescent relationships and ethnic identity was investigated in a sample of 414 adolescents from Latin American and Asian backgrounds. HL proficiency, but not language use, was positively associated with the quality of parent–adolescent relationships. Although HL proficiency and language use were both associated with ethnic identity, when taken together, only HL proficiency was a reliable predictor. These findings indicate that it is the development of proficiency in the HL that influences adolescents' successful adjustment, rather than their choice of languages. It is therefore important to support HL development in order to help immigrant-background students to better cope with the stresses of adolescence.     

Confidence intervals for nonparametric quantile regression: an emphasis on smoothing splines approach

In this paper we consider the problem of constructing confidence intervals for nonparametric quantile regression with an emphasis on smoothing splines. The mean‐based approaches for smoothing splines of Wahba (1983) and Nychka (1988) may not be efficient for constructing confidence intervals for the underlying function when the observed data are non‐Gaussian distributed, for instance if they are skewed or heavy‐tailed. This paper proposes a method of constructing confidence intervals for the unknown τth quantile function (0<τ<1) based on smoothing splines. In this paper we investigate the extent to which the proposed estimator provides the desired coverage probability. In addition, an improvement based on a local smoothing parameter that provides more uniform pointwise coverage is developed. The results from numerical studies including a simulation study and real data analysis demonstrate the promising empirical properties of the proposed approach.