Why Did House Members Vote for H.R. 4437?1

This article examines why members of the U.S. House of Representatives voted for H.R. 4437, the controversial 2005 bill to construct a 700‐mile immigration barrier along the U.S.‐Mexican border and to criminalize illegal presence and aid to undocumented immigrants. Logit analysis suggests that being a first‐term House member or a Republican and representing a district that was in the South or the West or heavily blue‐collar substantially boosted the odds of supporting H.R. 4437. If a member's district was disproportionately Asian, Latino, or, especially, African American, he or she was instead more likely to oppose the measure.     

Empowering part-time nurses in the treatment of depressed inpatients.

1. With the consistent number of part-time nurses in the workforce, hospitals would benefit by more actively integrating them into professional nursing practice. 2. Empowering part-time nurses by affording them the opportunity to provide primary care has the potential to effectively use part-time personnel, decrease the workload for full-time staff, offer more flexibility in scheduling, and result in savings for hospitals in terms of nursing recruitment and retention. 3. This program has successfully developed and implemented a model of primary nursing that places three part-time nurses on a team capable of handling two to three primary patients. The success of this model has been attributed to excellent communication, trust in one another's professional skills, and nursing expertise.     

Liability in child welfare

Child welfare workers and agencies are vulnerable to lawsuits. Recent court rulings have more clearly defined the liability of workers. The distinguishing variable is custody. Children injured while in the custody of the state are entitled to sue for damages. Children injured by their parent, even if under the supervision of a child welfare agency, are not entitled to claim a violation of their 14th Amendment rights. These cases are reviewed and strategies designed to minimize vulnerability are offered.     

Sex differences in nonverbal expressiveness: Emotional expression,personality, and impressions

Sex differences in expressiveness are well documented, but the reasons for and correlates of these important differences are not well studied. A comprehensive set of emotion-relevant personality measures was administered to 40 female and 39 male undergraduate participants, who were also videotaped in three situations: engaging in natural social interaction, describing a past emotional experience, and posing various emotions. Videotapes were judged by sets of naive observers as to emotion communicated and overall impression. Expressive females, who appeared friendly and dominant in social interaction, were found to have a hostile/aggressive personality (but this was not true of males). Expressive females also tended to look angry/disgusted when describing happy and sad experiences. The findings suggest that nonverbally skilled, charismatic women (but not men) may often possess a dominant/aggressive but self-controlled personality, in a new twist on the theory that sex differences in expressiveness result in part from the oppression of women in society.This research was supported in part by an intramural research grant from University of California, Riverside.     

Four‐Month‐Olds' Discrimination of Voice Changes in Multimodal Displays as a Function of Discrimination Protocol

Past studies have found equivocal support for the ability of young infants to discriminate infant‐directed (ID) speech information in the presence of auditory‐only versus auditory + visual displays (faces + voices). Generally, younger infants appear to have more difficulty discriminating a change in the vocal properties of ID speech when they are accompanied by faces. Forty 4‐month‐old infants were tested using either an infant‐controlled habituation procedure (Experiment 1) or a fixed‐trial habituation procedure (Experiment 2). The prediction was that the infant‐controlled habituation procedure would be a more sensitive measure of infant attention to complex displays. The results indicated that 4‐month‐old infants discriminated voice changes in dynamic face + voice displays depending on the order in which they were viewed during the infant‐controlled habituation procedure. In contrast, no evidence of discrimination was found in the fixed‐trial procedure. The findings suggest that the selection of experimental methodology plays a significant role in the empirical observations of infant perceptual abilities.     

Exposure Reconstruction for the TCDD-Exposed NIOSH Cohort Using a Concentration- and Age-Dependent Model of Elimination

Recent studies demonstrating a concentration dependence of elimination of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) suggest that previous estimates of exposure for occupationally exposed cohorts may have underestimated actual exposure, resulting in a potential overestimate of the carcinogenic potency of TCDD in humans based on the mortality data for these cohorts. Using a database on U.S. chemical manufacturing workers potentially exposed to TCDD compiled by the National Institute for Occupational Safety and Health (NIOSH), we evaluated the impact of using a concentration- and age-dependent elimination model (CADM) (Aylward et al., 2005) on estimates of serum lipid area under the curve (AUC) for the NIOSH cohort. These data were used previously by Steenland et al. (2001) in combination with a first-order elimination model with an 8.7-year half-life to estimate cumulative serum lipid concentration (equivalent to AUC) for these workers for use in cancer dose-response assessment. Serum lipid TCDD measurements taken in 1988 for a subset of the cohort were combined with the NIOSH job exposure matrix and work histories to estimate dose rates per unit of exposure score. We evaluated the effect of choices in regression model (regression on untransformed vs. ln-transformed data and inclusion of a nonzero regression intercept) as well as the impact of choices of elimination models and parameters on estimated AUCs for the cohort. Central estimates for dose rate parameters derived from the serum-sampled subcohort were applied with the elimination models to time-specific exposure scores for the entire cohort to generate AUC estimates for all cohort members. Use of the CADM resulted in improved model fits to the serum sampling data compared to the first-order models. Dose rates varied by a factor of 50 among different combinations of elimination model, parameter sets, and regression models. Use of a CADM results in increases of up to five-fold in AUC estimates for the more highly exposed members of the cohort compared to estimates obtained using the first-order model with 8.7-year half-life. This degree of variation in the AUC estimates for this cohort would affect substantially the cancer potency estimates derived from the mortality data from this cohort. Such variability and uncertainty in the reconstructed serum lipid AUC estimates for this cohort, depending on elimination model, parameter set, and regression model, have not been described previously and are critical components in evaluating the dose-response data from the occupationally exposed populations.     

A Numerical Solution to the Nonhomogeneous Two-Stage MVK Model of Cancer

In this article, we describe a straightforward method for solving the probability of at least one malignant cell by time t, and the associated hazard function, in the general (i.e., nonhomogeneous) two-stage Moolgavkar-Venzon-Knudson (MVK) model of cancer. The method consists of solving four coupled ordinary differential equations derived from the Kolmogorov backward equations for this process. The relationship of this method to previously proposed solutions is discussed.     

Joint impact of multiple observations on a subset of variables in multiple linear regression

In multiple linear regression analysis, each observation affects the fitted regression equation differently and has varying influences on the regression coefficients of the different variables. Chatterjee & Hadi (1988) have proposed some measures such as DSSE_ij (Impact on Residual Sum of Squares of simultaneously omitting the ith observation and the jth variable), F_j (Partial F-test for the jth variable) and F_j(i) (Partial F-test for the jth variable omitting the ith observation) to show the joint impact and the interrelationship that exists among a variable and an observation. In this paper we have proposed more extended form of those measures DSSE_IJ, F_J and F_J(I) to deal with the interrelationships that exist among the multiple observations and a subset of variables by monitoring the effects of the simultaneous omission of multiple variables and multiple observations.