The vicious circle: effects of race and class on university entrance in Brazil

Brazil has high levels of socio-economic inequality and an inequitable distribution of access to higher education. How much of this inequality is associated with race or class is an important question in light of the current debate over affirmative action and the suitability of race and social targeted policies. There are those who claim that racial disparities in the educational system are a result of students’ social status and not a result of racism, while others believe race is an important factor that superposes the effect of class. This study uses national survey data from Brazil’s Exame Nacional do Ensino Médio (National Secondary Education Exam [ENEM]) to examine the relationship between race and access to higher education of high school students between 2004 and 2008. The results document a vicious circle which connects the schooling of the young with their race, socio-economic status, and university attendance.     

The Structured Interview of Family Assessment Risk: Convergent Validity,Inter-rater Reliability and Structural Relations

The quality of parenting, composition and socio-economic status are family risk or protective factors on juvenile delinquency, however, there is not an instrument to help psychologists and social workers to specifically assess the adolescent offender’s family. This study set out to accomplish an additional validation study of the structured interview of family assessment risk (SIFAR), a structured professional judgment tool for the assessment of family risk and protective factors of juvenile delinquents. The statistical analyses included inter-rater reliability, convergent validity with YLS/CMI, the Partial Least Squares approach to structural equation modeling and receiving operator characteristics (ROC) analysis. A sample of 130 male adolescent delinquents detained in Portuguese forensic facilities and their parents, were paired analyzed. The YLS/CMI was used to analyze the convergent validity with SIFAR. SIFAR shows a strong correlation with the YLS/CMI family context, moderate to high values of inter-rater reliability; SIFAR factors show that they are predictive determinants of the Moderate Four risk factors. ROC analysis shows adequate accuracy power. The findings show that SIFAR it is useful as an additional assessment tool for structured risk assessment instruments since it allows understanding the vulnerabilities and strengths of the delinquent’s family.     

Controversies and challenges of ritual abuse

Children who have survived ritual abuse have endured physical, psychological, and sexual trauma; brain-washing; and mind-altering drugs. Their trust in adults has been eroded. Their coping strategies include anxiety, denial, self-hypnosis, dissociation, and self-mutilation. Although reports of ritual abuse initially seem hard to believe, nurses have a responsibility to detect clues to abuse, diagnose the child's responses, and recognize controversial issues regarding ritual abuse. To evaluate ritual abuse, nurses should avoid interview strategies that influence the child's recall (e.g., coaching, suggestions) and recognize that some reports are discounted as false memories because they emerge from fantasy, distortions, innocent deceptions, false beliefs, lies, or adult coaching. Nurses play an important role in case finding and treatment. They can evaluate clues to ritual abuse to reduce sources of error in assessment, build a child's trust, monitor their own attitudes toward ritual abuse, and intervene to increase self-esteem, empathy, boundary establishment, and coping. Nurses have an important opportunity to detect and begin healing the wounds caused by a child's abuse.     

A Structural Equation Model Estimation of the Role of Social Vulnerability as a Predictor of People’s Feelings of Unsafety

Social Indicators Research - People’s perception of insecurity is linked to a wide range of factors and up-to-date sources stress the impact of socially constructed concerns on feelings of...     

Hypnosis for pain management

Nurses are in a key position to learn and use hypnosis with patients to reduce pain and enhance self-esteem. However, most nurses lack knowledge about the clinical effectiveness of hypnosis and may seek continuing education to become skilled in its use. Painful procedures, treatments, or diseases remain a major nursing challenge, and nurses need complementary ways to relieve pain from surgery, tumors, injuries, and chemotherapy. This article examines the evidence base related to hypnosis for pain management, as well as how to assess and educate patients about hypnosis.     

The Network Autocorrelation Model using Two-mode Data: Affiliation Exposure and Potential Bias in the Autocorrelation Parameter

The network autocorrelation model has been a workhorse for modeling network influences on individual behavior. The standard network approaches to mapping social influence using network measures, however, are limited to specifying an influence weight matrix (W) based on a single mode network. Additionally, it has been demonstrated that the estimate of the autocorrelation parameter ρ of the network effect tends to be negatively biased as the density in W matrix increases. The current study introduces a two-mode version of the network autocorrelation model. We then conduct simulations to examine conditions under which bias might exist. We show that the estimate for the affiliation autocorrelation parameter (ρ) tends to be negatively biased as density increases, as in the one-mode case. Inclusion of the diagonal of W, the count of the number of events participated in, as one of the variables in the regression model helps to attenuate such bias, however. We discuss the implications of these results.     

Collaboration and competition in a children's health initiative coalition: a network analysis

Activating communities to achieve public health change and initiate policy reform usually requires collective action from many entities. This case study analyzes inter-organizational networks among members of a coalition created to expand health insurance coverage to uninsured children in a large metropolitan area. Six networks were measured: collaboration, competition, formal agreements, receive funding from, send funding to, and greater communication. The response rate was 65.8% (50 of the 76 active members). Positive network questions such as “who do you collaborate with” elicited many network choices whereas negative ones such as “who do you compete with” elicited few. The collaboration network had a core–periphery structure and analysis showed that a large network can be reduced to a small set of core organizations one-sixth the size of the whole. Centrality (out- and in-degree) was associated with perceived organizational function and perceived barriers to success. For example, organizations that received many choices as collaboration partners were more likely to perceive the coalition functioned well than those who received few choices. The study suggests that perceptions of organizational performance are associated with position in the network, central members are more likely to perceive the organization performs well than those on the periphery.     

Asymptotic Inference for Performance Fees and the Predictability of Asset Returns

In this article, we provide analytical, simulation, and empirical evidence on a test of equal economic value from competing predictive models of asset returns. We define economic value using the concept of a performance fee—the amount an investor would be willing to pay to have access to an alternative predictive model used to make investment decisions. We establish that this fee can be asymptotically normal under modest assumptions. Monte Carlo evidence shows that our test can be accurately sized in reasonably large samples. We apply the proposed test to predictions of the U.S. equity premium.