A study on different experimental configurations for age, race, and gender estimation problems

This paper presents a detailed study about different algorithmic configurations for estimating soft biometric traits. In particular, a recently introduced common framework is the starting point of the study: it includes an initial facial detection, the subsequent facial traits description, the data reduction step, and the final classification step. The algorithmic configurations are featured by different descriptors and different strategies to build the training dataset and to scale the data in input to the classifier. Experimental proofs have been carried out on both publicly available datasets and image sequences specifically acquired in order to evaluate the performance even under real-world conditions, i.e., in the presence of scaling and rotation

Framing Ethnic Variations in Alcohol Outcomes from Biological Pathways to Neighborhood Context

Background Health disparities research seeks to eliminate disproportionate negative health outcomes experienced in some racial/ethnic minority groups. This brief review presents findings on factors associated with drinking and alcohol‐related problems in racial/ethnic groups. Methods Those discussed are as follows: (i) biological pathways to alcohol problems, (ii) gene × stress interactions, (iii) neighborhood disadvantage, stress, and access to alcohol, and (iv) drinking cultures and contexts. Results These factors and their interrelationships are complex, requiring a multilevel perspective. Conclusions The use of interdisciplinary teams and an epigenetic focus are suggested to move the research forward. The application of multilevel research to policy, prevention, and intervention programs may help prioritize combinations of the most promising intervention targets

Preferences for redistribution around the world

Gender, income, education and self-employment are robust predictors for individual support for redistribution in the OECD. In addition, considerations of social status, the fairness of the allocation mechanism, perceived moral worth of the poor and individual autonomy are important. The results for the OECD are compared to those for a large sample of non-OECD countries which also include less developed economies. Neither gender, nor self-employment, nor fairness considerations exhibit a robust association with preferences for redistribution. However, education, income, individual autonomy and moral worth of the poor remain important determinants. On average, preferences for redistribution indicate that within the OECD, there is no desire to change redistributive policies. In contrast, in the sample of non-OECD countries, on average there is a desire to redistribute less. --preferences for redistribution,social rivalry effect,social identity,survey data,World Values Survey

DECISIONS LEADING TO INEQUALITIES IN THE JUVENILE JUSTICE SYSTEM: USING DATA TO PREDICT DELINQUENT OUTCOMES, INFORM DECISIONS, AND REDUCE DISPARITIES FOR JUSTICE-INVOLVED YOUTH

This dissertation focuses on how decisions are made in the juvenile justice system and what strategies can be used to make more informed decisions in the future, in three separate investigations. (1) To begin, eight years of initial detention decisions (N=26,128) were collected to determine what factors affect the arresting officers’ decision to detain youth at arrest. Findings reveal that the severity of current offense and prior offending history are the greatest predictors of initial detention. However, results demonstrate that race and the distance from a detention facility also influence these decisions. Non-white youth are more likely detained than their white counterpart holding relevant factors constant. Additionally, the closer an arrest takes place to a detention facility the more likely a youth is detained. This geographical variable is unique to this analysis and is found to mediate the effect that other geographic variables have on detention decisions (rural/urban classification). Also, evidence suggests that there is a greater disparity in the use of initial detention between white and non-white youth in areas that are closer in proximity to a detention facility. (2) Next, this investigation utilized six years of juvenile intakes (N=3,121) to create and validate a juvenile risk screener to predict recidivism in a one year period of risk. Items included in the risk screener were selected based on a series of bivariate and multivariate analyses. Out of the 246 risk factors eligible for the screener, seven factors were found to be important predictors for recidivism and were included in the risk screener. Validation measurements demonstrate comparable, and at times increased, prediction accuracy from the currently used, significantly larger risk assessment. (3) The final study analyzes an experimental method of weighting risk factors using conjunctive analysis of case configuration (CACC). This study demonstrates the importance of risk factor combinations and how these combinations affect the outcome. Using this weighting strategy, results found slight improvement in prediction accuracy over a simpler 0, 1 scoring method and a more complex score from logistic regression

Audits as Evidence: Experiments, Ensembles, and Enforcement

We develop tools for utilizing correspondence experiments to detect illegal discrimination by individual employers. Employers violate US employment law if their propensity to contact applicants depends on protected characteristics such as race or sex. We establish identification of higher moments of the causal effects of protected characteristics on callback rates as a function of the number of fictitious applications sent to each job ad. These moments are used to bound the fraction of jobs that illegally discriminate. Applying our results to three experimental datasets, we find evidence of significant employer heterogeneity in discriminatory behavior, with the standard deviation of gaps in job-specific callback probabilities across protected groups averaging roughly twice the mean gap. In a recent experiment manipulating racially distinctive names, we estimate that at least 85% of jobs that contact both of two white applications and neither of two black applications are engaged in illegal discrimination. To assess the tradeoff between type I and II errors presented by these patterns, we consider the performance of a series of decision rules for investigating suspicious callback behavior under a simple two-type model that rationalizes the experimental data. Though, in our preferred specification, only 17% of employers are estimated to discriminate on the basis of race, we find that an experiment sending 10 applications to each job would enable accurate detection of 7-10% of discriminators while falsely accusing fewer than 0.2% of non-discriminators. A minimax decision rule acknowledging partial identification of the joint distribution of callback rates yields higher error rates but more investigations than our baseline two-type model. Our results suggest illegal labor market discrimination can be reliably monitored with relatively small modifications to existing audit designs

ILR Faculty Publications 2012-13

The production of scholarly research continues to be one of the primary missions of the ILR School. During a typical academic year, ILR faculty members published or had accepted for publication over 25 books, edited volumes, and monographs, 170 articles and chapters in edited volumes, numerous book reviews. In addition, a large number of manuscripts were submitted for publication, presented at professional association meetings, or circulated in working paper form. Our faculty's research continues to find its way into the very best industrial relations, social science and statistics journals.Faculty_Publications_2012_13.pdf: 77 downloads, before Oct. 1, 2020