Michael W. Spiller

Employers Gone Rogue: Explaining Industry Variation in Violations of Workplace Laws

Drawing on an innovative, representative survey of workers in Chicago, Los Angeles, and New York City, the authors analyze minimum wage, overtime, and other workplace violations in the low-wage labor market. They document significant interindustry variation in both the mix and the prevalence of violations, and they show that while differences in workforce composition are important in explaining that variation, differences in job and employer characteristics play the stronger role. The authors suggest that industry noncompliance rates are shaped by both product market and institutional characteristics, which together interact with labor supply and the current weak penalty and enforcement regime in the United States. They close with a research agenda for this still-young field, framing noncompliance as an emerging strategy in the reorganization of work and production at the bottom of the U.S. labor market.

Unmasking health determinants and health outcomes for urban First Nations using respondent-driven sampling

Objective Population-based health information on urban Aboriginal populations in Canada is limited due to challenges with the identification of Aboriginal persons in existing health data sets. The main objective of the Our Health Counts (OHC) project was to work in partnership with Aboriginal stakeholders to generate a culturally relevant, representative baseline health data set for three urban Aboriginal communities in Ontario, Canada. Design Respondent-driven sampling (RDS). Setting Hamilton, Ontario, Canada. Participants The OHC study, in partnership with the De dwa da dehs ney >s Aboriginal Health Access Centre (DAHC), recruited 554 First Nations adults living in Hamilton using RDS. Results Among First Nations adults living in Hamilton, 78% earned less than

Respondent-Driven Sampling – Testing Assumptions: Sampling with Replacement

20 000 per year and 70% lived in the lowest income quartile neighbourhoods. Mobility and crowded living conditions were also highly prevalent. Common chronic diseases included arthritis, hypertension, diabetes and chronic obstructive pulmonary disease and rates of emergency room access were elevated. Conclusions RDS is an effective sampling method in urban Aboriginal contexts as it builds on existing social networks and successfully identified a population-based cohort. The findings illustrate striking disparities in health determinants and health outcomes between urban First Nations individuals and the general population which have important implications for health services delivery, programming and policy development.

Women’s Wage Theft

Abstract Classical Respondent-Driven Sampling (RDS) estimators are based on a Markov Process model in which sampling occurs with replacement. Given that respondents generally cannot be interviewed more than once, this assumption is counterfactual. We join recent work by Gile and Handcock in exploring the implications of the sampling-with-replacement assumption for bias of RDS estimators. We differ from previous studies in examining a wider range of sampling fractions and in using not only simulations but also formal proofs. One key finding is that RDS estimates are surprisingly stable even in the presence of substantial sampling fractions. Our analyses show that the sampling-with-replacement assumption is a minor contributor to bias for sampling fractions under 40%, and bias is negligible for the 20% or smaller sampling fractions typical of field applications of RDS.

All Work and No Pay: Violations of Employment and Labor Laws in Chicago, Los Angeles and New York City

In this study, the authors identify and analyze a distinct and understudied source of gender inequality: gender differences in violations of wage-related workplace laws. The authors find that women have significantly higher rates of minimum wage and overtime violations than men and also lose more of their earnings to wage theft than men. In the case of minimum wage violations, the authors also find that nativity and immigration status strongly mediate this gender difference. Multivariate analysis suggests that demand-side characteristics—occupation and measures of nonstandard work and informality—account for more of the gender difference in minimum wage violations than do worker characteristics.