Der Differences in Attitudes toward Unions

Abstract

In the U.S. private sector, women are less likely than men to be union members. This study analyzes a unique national survey (conducted in 1984) to determine if women are less interested than men in unionizing or if, instead, they are equally interested but face higher barriers to unionization. The results support the latter interpretation. In particular, nonunion women in private sector white-collar jobs (representing over half of the female nonunion work force) expressed more interest than comparable men in joining unions. This finding appears to reflect more optimism among the women in this group than among the men about what unions can accomplish; it is not explained by gender differences in attitudes toward jobs or employers. The authors discount theories that family responsibilities, or concerns of female workers that set them apart from men, present special barriers to unionization.

The association between union membership and perceptions of safety climate among US adult workers

“…Covariates were selected based on what was supported in the literature as being factors of safety climate and union membership, as well as taking into consideration whether the variable was collected in the QWL. The available literature identifies sex, race, age, education, private vs. public sector, work status, and state of residence being strong indicators of union membership with males, non-whites, those middle-aged, individuals who were high school graduates or had some college education, those who worked in the public sector and government, full-time employees, and individuals from certain states (e.g., Hawaii, New Jersey, New York, Washington), respectively, having greater likelihood of being in a union ( Bureau of Labor Statistics, 2018a , Benson and Griffin, 1988 , Hirsch and Berger, 1984 , Hirsch et al, 2001 , Hundley, 1988 , Kokkelenberg and Sockell, 1985 , Mishel, 2012 , Schur and Kruse, 1992 , Silverblatt and Amann, 1991 ;). Following the literature, individual demographics included in the analysis were: age (18–29, 30–39, 40–49, 50–64, 65 and above), sex (male or female), educational level (less than a high school diploma, high school graduate, some college/associate’s degree, bachelor’s degree, or beyond bachelor’s degree), work status (part- or full-time), race/ethnicity (non-Hispanic white, non-Hispanic black, and other/unclassified), region of residence (northeast, Midwest, south, west), and respondent annual income ($1-$9,999, $10,000-$14,999, $15,000-$19,999, $20,000-$24,999, or $25,000 and greater).…”

“…The study matched participants based on demographic factors (age, sex, education, race/ethnicity, region) and likelihood of being in a union (work status, respondent income, private vs. public sector, industry) as stated above ( Bureau of Labor Statistics, 2018a , Benson and Griffin, 1988 , Hirsch and Berger, 1984 , Hirsch et al, 2001 , Hundley, 1988 , Kokkelenberg and Sockell, 1985 , Mishel, 2012 , Schur and Kruse, 1992 , Silverblatt and Amann, 1991 ). The study utilized 1:3 nearest-neighbor matching so that each treated unit could be matched to more than one control since the unmatched treatment and control group had a notable difference in numbers (n = 634 and n = 6,655); nearest-neighbor 1:3 matching was used because the matched units reached saturation beyond one-to-three matching.…”