Segmented Assimilation,Local Context and Determinants of Drug Violence in Miami and San Diego: Does Ethnicity and Immigration Matter?1

Does the ethnic and immigrant composition of a community and existence of immigrant enclaves or barrios influence community level drug violence? This study explores the relationship between these and other factors in Miami and San Diego census tracts. We employ data about the distribution of Cubans, Central Americans, Haitians, Mexicans and Southeast Asians, controlling for social and economic influences of drug versus non‐drug violence. We also analyze the impact of various waves of immigration and immigrant communities to understand the circumstances under which drug violence occurs or is limited at the census tract level. The findings lend some support to the positive and negative aspects of Portes and Rumbaut's (2001) segmented assimilation hypothesis in Miami and San Diego neighborhoods. The strength of this conclusion varies and is contingent upon ethnic composition, new versus old immigration, and the all‐encompassing effects of economic deprivation     

A DIAGNOSIS FOR OUR TIMES:

This paper explores two submerged networks in the Pittsburgh area alternative health movement through the use of thirty two intensive interviews and ethnographic research. Utilizing Jürgen Habermas's colonization theory as well as Alberto Melucci's emphasis on the process of collective identity formation, the paper describes a "conservative Christian' and a culturally progressive network demonstrating how these networks differ and what they have in common. The paper examines how new oppositional identities and meanings emerge from face to face interactions between alternative practitioners, patients and activists in a variety of settings. Overall, the paper argues that resistance to the "medical industrial complex,' one leading instrument of "colonization,' is coming from the Christian right as well as elements of the cultural left.     

Deserts and oases: the continuing concentration of population in the American Mountain West

The Mountain West is a region that seems to be simultaneously rural and urban. With its wide-open spaces, many national parks, monuments, and forests, and high degree of federal land ownership the West appears as the quintessential rural area. However, over 70 percent of the West's population live in metropolitan areas. This simultaneous rural and urban nature of the West is important in understanding the changing population geography of the region. We examine this by focusing on changing patterns of population concentration among metro and nonmetro counties. Unlike other regions in the US, the Mountain West has never experienced a period of counterurbanization or population deconcentration. Not only is current in-migration to the region increasingly concentrated in old and new metro areas, it is also concentrated in a select number of nonmetro areas as well—particularly nonmetro counties adjacent to metro areas, in retirement destinations, and in recreation centers.     

CONCENTRATED POVERTY, RACE, AND HOMICIDE

Research on the link between levels of poverty and homicide in urban areas has persistently reported the existence of a relationship for whites but not for blacks. This is despite the fact that most analysts expect that the higher levels of urban black homicide are due in part to the higher levels of urban black poverty. The present research introduces a more meaningful, spatially based measure of concentrated poverty and argues that the effect of concentrated poverty on homicide rates should be the same for both racial groups. The hypotheses are tested with race-disaggregated data for a sample of central cities circa 1990. The results suggest that, when poverty is measured as a linear spatially based phenomenon, in is a more important determinat of race-specific homicide rates than overall city levels of disadvantage and that the concentration of poverty increases both black and white homicide rather equally.     

USING LINEAR PREDICTORS TO IMPUTE ALLELE FREQUENCIES FROM SUMMARY OR POOLED GENOTYPE DATA

Recently-developed genotype imputation methods are a powerful tool for detecting untyped genetic variants that affect disease susceptibility in genetic association studies. However, existing imputation methods require individual-level genotype data, whereas in practice it is often the case that only summary data are available. For example this may occur because, for reasons of privacy or politics, only summary data are made available to the research community at large; or because only summary data are collected, as in DNA pooling experiments. In this article, we introduce a new statistical method that can accurately infer the frequencies of untyped genetic variants in these settings, and indeed substantially improve frequency estimates at typed variants in pooling experiments where observations are noisy. Our approach, which predicts each allele frequency using a linear combination of observed frequencies, is statistically straight-forward, and related to a long history of the use of linear methods for estimating missing values (e.g. Kriging). The main statistical novelty is our approach to regularizing the covariance matrix estimates, and the resulting linear predictors, which is based on methods from population genetics. We find that, besides being both fast and flexible - allowing new problems to be tackled that cannot be handled by existing imputation approaches purpose-built for the genetic context - these linear methods are also very accurate. Indeed, imputation accuracy using this approach is similar to that obtained by state-of-the art imputation methods that use individual-level data, but at a fraction of the computational cost.     

A Preliminary Investigation of the Reinforcement Function of Signal Detections in Simulated Baggage Screening: Further Support for the Vigilance Reinforcement Hypothesis

The vigilance reinforcement hypothesis (VRH) asserts that errors in signal detection tasks are partially explained by operant reinforcement and extinction processes. VRH predictions were tested with a computerized baggage screening task. Our experiment evaluated the effects of signal schedule (extinction vs. variable interval 6 min) and visual field complexity (dial vs. baggage x-ray) on search behavior rates. There was a main effect for signal schedule [F (1, 20) = 14.0, p = .001, p_rep = 0.99], but no effects for field complexity or interaction. The VRH suggests that performance errors in visual screening work may be reduced through operant conditioning of search behaviors by intensive management of artificially planted signals.     

Irishness in Glasgow, 1863–70

In early November 1914 the German military authorities ordered the internment of all British male civilians aged between 17 and 55 then still resident in Germany. Over four thousand British subjects were affected by this measure. This article examines the domestic political background to the decision in favour of internment, focusing on the role of public opinion and of competing voices within the German war leadership. It also looks at attempts to negotiate the release and exchange of civilian prisoners after 1914. Internment was supported by the military and by most sections of the middle-class press. While partly a reaction to similar measures against Germans in Britain, it also reflected the government's growing frustration at the failure to achieve victory in the opening months of the war.     

Multivariate sufficient statistics using Kronecker products

We present a multivariate sufficient statistic using Kronecker products that dramatically increases computational efficiency in evaluating likelihood functions and/or posterior distributions. In particular, we examine the example of multivariate regression in a Bayesian setting. We compare the computation time for using the Gibbs sampler both with and without the sufficient statistic. We show that the difference in computation time grows quadratically with the number of covariates and products and linearly with the number of individuals. In the simulation study, speedup factors ranging from at least 20 times to almost 300 times were observed when using the Kronecker sufficient statistic.