On the robustness of the generalized fused lasso to prior specifications

Using networks as prior knowledge to guide model selection is a way to reach structured sparsity. In particular, the fused lasso that was originally designed to penalize differences of coefficients corresponding to successive features has been generalized to handle features whose effects are structured according to a given network. As any prior information, the network provided in the penalty may contain misleading edges that connect coefficients whose difference is not zero, and the extent to which the performance of the method depend on the suitability of the graph has never been clearly assessed. In this work we investigate the theoretical and empirical properties of the adaptive generalized fused lasso in the context of generalized linear models. In the fixed \(p\) setting, we show that, asymptotically, adding misleading edges in the graph does not prevent the adaptive generalized fused lasso from enjoying asymptotic oracle properties, while forgetting suitable edges can be more problematic. These theoretical results are complemented by an extensive simulation study that assesses the robustness of the adaptive generalized fused lasso against misspecification of the network as well as its applicability when theoretical coefficients are not exactly equal. Our contribution is also to evaluate the applicability of the generalized fused lasso for the joint modeling of multiple sparse regression functions. Illustrations are provided on two real data examples.     

The West,Russia, and China in Central Asia: What Kind of Game Is Being Played in the Region?

The article discusses the nature of the tangled interaction between the ex-Soviet Central Asian republics and the outside great powers – Russia, the United States and China. Although the so-called Great Game model is often used to explain the geopolitical rivalry in the region, the current pattern of relations between various international actors is much more complex than a traditional tug-of-war between the old colonial empires. While Russia's strategic role in Central Asia appears to be on the rise, the capacity of the West to influence political developments in the region has diminished. However, the overall situation in Central Asia remains volatile and its geopolitical landscape is far from being settled.     

Modeling Demand For Unionization With Nontraditional Data Analysis Methods

Upon reviewing the extant literature on determinants of unionism, it becomes clear that many areas that have had a plethora of research attention do not converge upon singularly directional findings. This study explores a potential cause of such an apparent anomaly: nonlinearity of data. An exploratory examination of correlation coefficients among typical union determinant variables seems to show different patterns of relationships at different levels of union demand. Thus, a break from traditional linear data analysis techniques is explored in the interest of explaining more variance with typical, theoretically derived variables by using neural network analysis. Results of analyses on industry level data reveal that using neural network analysis to model union demand explained over four times as much variance as multiple regression analysis.     

Disagreement over the immigration of low-income earners in a welfare state

This paper studies natives’ economically motivated preferences over different levels of immigration of low-income earners. Immigration affects natives through both intra- and intergenerational redistribution programmes and in the labour market. Our analysis suggests, in a welfare state that looks after the poor and the aged, economic motivation does not necessarily lead a native to have an extreme opinion on the preferable level of immigration, although it causes disagreement among natives. We find, regardless of parameter values, high-income earners prefer at least as much immigration as low-income earners who, in turn, prefer at least as much immigration as pensioners. The median voter is then likely to be a low-income native.

Differential Recovery Migration across the Rural–Urban Gradient: Minimal and Short-Term Population Gains for Rural Disaster-Affected Gulf Coast Counties

Places affected or threatened by extreme environmental disturbances confront a number of significant issues, including whether their populations will stay the same or change through migration. Research on Hurricanes Katrina and Rita shows some displaced residents returned to their disaster-affected communities once the built environment was restored, new migrants settled in affected places as part of the rebuilding effort, and the regional migration system grew more urbanized and spatially concentrated during post-disaster years. Research also shows that not all disaster-affected places recovered their populations. Our study examines whether differential recovery is systematically patterned along the rural–urban gradient. Using U.S. Census Bureau estimates and IRS county-to-county migration data, we investigate whether the 2005 hurricane season differentially exacerbated or altered previous migration trends across a rural–urban gradient that incorporates proximity to metropolitan areas and disaster-related housing loss. We find a rural–urban differential in Gulf Coast recovery migration: The disaster boosted migration among non-metropolitan counties, yet these increases were smaller and short-lived compared to the patterns found for metropolitan counties, most especially high loss metropolitan counties. Our findings encourage theories of environmental migration to incorporate spatial differentiation and scenarios of environmental changes to account for differential impacts on settlement patterns across the rural–urban continuum.     

“To get the word out”: LGBTQ+ Young adults’ motivations for participating in qualitative research studies

Understanding why socially marginalized individuals, such as lesbian, gay, bisexual, transgender and/or queer (LGBTQ+) people, participate in research can improve qualitative research designs, as well as social services and policies. In providing a participant-centered foundation, we interviewed 65 LGBTQ+ young adults and asked “Why are certain LGBTQ+ young adults motivated to engage in qualitative social science studies?” Many LGBTQ+ young people said they were committed to enacting social change and promoting advocacy. Participants also highlighted supporting scientific research and knowledge production. Finally, LGBTQ?+ participants engaged with research to introspectively analyze their identity development processes. These findings can facilitate access to socially vulnerable and underrepresented groups through a methodological focus on participant benefits.     

Does it get better? LGBTQ social work students and experiences with harmful discourse

Although the field of social work is grounded in social justice, the social work educational experience, including classrooms, may not live up to this value, especially for lesbian, gay, bisexual, transgender, and queer (LGBTQ) students. Using a qualitative phenomenological approach, this study examined the experiences of harmful discourse in social work classrooms for LGBTQ students. Findings indicate that students experienced being misgendered, tokenized, and erased through cis-/heteronormative language and classroom teachings. Although social work is guided by frameworks of social justice, microaggressions and discrimination may be vaguely glossed over, if addressed at all. This study highlights the gap between the values social work teaches and how social work education is delivered.     

Effects of demography and urbanization on stress and body condition in urban white-tailed deer

Urban Ecosystems - White-tailed deer (Odocoileus virginianus) are becoming increasingly common in urban environments. How they respond to potential changes (i.e. increased human interactions,...