scholarly journals Are U.S. Professionals and Managers More Left Than Blue-Collar Workers? An Analysis of the General Social Survey, 1974 to 2018

2022 ◽  
Vol 8 ◽  
pp. 237802312110686
Author(s):  
Steven Brint ◽  
Michaela Curran ◽  
Matthew C. Mahutga
Keyword(s):  
Criminal Justice ◽  
Social Science ◽  
Social Economic ◽  
Political Identity ◽  
General Social Survey ◽  
Blue Collar ◽  
Social Survey ◽  
Science Interest ◽  
Blue Collar Workers ◽  
Political Differences

Social science interest in professionals and managers as a left- and liberal-trending stratum has increased in recent years. Using General Social Survey data over a 44-year period, the authors examine 15 attitudes spanning social, economic, and political identity liberalism. On nearly all attitudes, professionals and managers have trended in a liberal direction, have liberalized more quickly than blue-collar workers, and are either as or more liberal than blue-collar workers. The authors find that the higher levels of education among professionals and managers, their tendency to adopt nonauthoritarian outlooks, and their lower propensity to identify with fundamentalist religion mediate their more liberal trends vis-à-vis blue-collar workers. Conversely, their higher relative incomes suppress the extent of their economic and criminal justice liberalism. The authors’ theorization links changes in the macro-economy to growing gaps in the composition of the two strata and the activities of politicians and parties to consolidate emerging political differences.

scholarly journals Advantages of Matched Over Unmatched Opt-in Samples for Studying Criminal Justice Attitudes: A Research Note

2020 ◽  
Author(s):  
Amanda Graham ◽  
Justin Pickett ◽  
Francis T. Cullen
Keyword(s):  
Criminal Justice ◽  
Data Quality ◽  
Recent Work ◽  
Multivariate Regression ◽  
General Social Survey ◽  
Prior Work ◽  
Similar Magnitude ◽  
Social Survey ◽  
Wrong Direction ◽  
Data Source

PURPOSE: Despite the growing popularity of online opt-in samples in criminology, recent work shows that resultant findings often do not generalize. Not all opt-in samples are alike, however, and matching may improve data quality. Replicating and extending prior work, we compare the generalizability of relational inferences from unmatched and matched opt-in samples.METHODS: Estimating identical models for four criminal justice outcomes, we compare multivariate regression results from national matched (YouGov) and unmatched (MTurk) opt-in samples to those from the General Social Survey (GSS). RESULTS: YouGov coefficients are almost always in the same direction as GSS coefficients, especially when statistically significant, and are mostly of a similar magnitude; less than 10% of the YouGov and GSS coefficients differ significantly. By contrast, MTurk coefficients are more likely to be in the wrong direction, more likely to be much larger or smaller, and are over twice as likely to differ significantly from GSS coefficients.CONCLUSIONS: Matched opt-in samples provide a relatively inexpensive data source for criminal justice researchers, compared to probability samples, and also appear to carry a smaller generalizability penalty than unmatched samples. Our study suggests relational inferences from matched opt-in samples are more likely to generalize than those from unmatched samples.

Political Identity and Confidence in Science and Religion in the United States

2020 ◽  
Vol 81 (4) ◽  
pp. 439-461
Author(s):  
Timothy L O’Brien ◽  
Shiri Noy
Keyword(s):  
United States ◽  
Political Identity ◽  
General Social Survey ◽  
The United States ◽  
Science And Religion ◽  
Public Perceptions ◽  
Social Survey ◽  
Political Identities ◽  
Moral Claims ◽  
The Relationship

Abstract This article investigates changes in public perceptions of science and religion in the United States between 1973 and 2018. We argue that the deepening ties between science and religion and opposing moral claims reconfigured the relationship between political identities and confidence in science and religion during this period. Our analysis of 30 waves of General Social Survey data finds that while Republicans once were more likely than Democrats to be more confident in science than religion, Democrats are now more likely to than Republicans. And, while Democrats used to be more likely than Republicans to be more confident in religion than science, this difference also reversed. These findings underscore the growing importance of political identities as predictors of confidence in science and religion and suggest that the politicization of science and religion fueled a perception that they provide not just alternative frameworks but opposing ones.

scholarly journals Advantages of Matched Over Unmatched Opt-in Samples for Studying Criminal Justice Attitudes: A Research Note

2020 ◽  
pp. 001112872097743
Author(s):  
Amanda Graham ◽  
Justin T. Pickett ◽  
Francis T. Cullen
Keyword(s):  
Criminal Justice ◽  
Data Quality ◽  
Recent Work ◽  
Multivariate Regression ◽  
General Social Survey ◽  
Prior Work ◽  
Similar Magnitude ◽  
Social Survey ◽  
Wrong Direction ◽  
Data Source

Despite the growing popularity of online opt-in samples in criminology, recent work shows that resultant findings often do not generalize. Not all opt-in samples are alike, however, and matching may improve data quality. Replicating and extending prior work, we compare the generalizability of relational inferences from unmatched and matched opt-in samples. Estimating identical models for four criminal justice outcomes, we compare multivariate regression results from national matched (YouGov) and unmatched (MTurk) opt-in samples to those from the General Social Survey (GSS). YouGov coefficients are almost always in the same direction as GSS coefficients, especially when statistically significant, and are mostly of a similar magnitude; less than 10% of the YouGov and GSS coefficients differ significantly. By contrast, MTurk coefficients are more likely to be in the wrong direction, more likely to be much larger or smaller, and are about three times as likely to differ significantly from GSS coefficients. Matched opt-in samples provide a relatively inexpensive data source for criminal justice researchers, compared to probability samples, and also appear to carry a smaller generalizability penalty than unmatched samples. Our study suggests relational inferences from matched opt-in samples are more likely to generalize than those from unmatched samples.

scholarly journals Does the public’s confidence in the scientific community affect its willingness to participate in social science research? A test examining the demeanor of survey respondents

2019 ◽  
Vol 12 (3) ◽  
pp. 205979911988428
Author(s):  
Christopher P Scheitle
Keyword(s):  
Social Sciences ◽  
Social Science ◽  
Scientific Community ◽  
Social Science Research ◽  
General Social Survey ◽  
Science Research ◽  
Willingness To Participate ◽  
Medical Sciences ◽  
Social Survey ◽  
The Social

Research examining the consequences of the public’s confidence in the scientific community has primarily focused on the natural or medical sciences. It is not clear whether the public’s confidence in the scientific community has implications for research and practice in the social sciences. To begin examining this question, this study assesses whether survey respondents’ confidence in the scientific community is associated with their demeanor during the survey interview. This is consequential because respondent demeanor itself has been associated with survey refusal and nonresponse to items within surveys. Analysis of the 2004–2016 General Social Survey finds that individuals expressing more confidence in the scientific community are rated as having more positive demeanors by interviewers. Respondents’ confidence in other types of institutions does not show the same association, suggesting that confidence in the scientific community is uniquely associated with respondents’ demeanor during the interview. These findings suggest that the public’s confidence in science could have implications for at least survey-based social science research.

GSS 2011 Linked with TIFF: Exploring the Cost of Child Care in Canada and the Use of the Child Care Tax Benefit

2019 ◽  
Vol 12 (1) ◽  
pp. 81-103
Author(s):  
Leanne Findlay ◽  
Dafna Kohen
Keyword(s):  
Child Care ◽  
General Social Survey ◽  
Cost Of Care ◽  
Indigenous Identity ◽  
Social Survey ◽  
The Cost ◽  
Care Costs ◽  
Compare And Contrast ◽  
Employment Characteristics ◽  
Different Sources

Affordability of child care is fundamental to parents’, in particular, women’s decision to work. However, information on the cost of care in Canada is limited. The purpose of the current study was to examine the feasibility of using linked survey and administrative data to compare and contrast parent-reported child care costs based on two different sources of data. The linked file brings together data from the 2011 General Social Survey (GSS) and the annual tax files (TIFF) for the corresponding year (2010). Descriptive analyses were conducted to examine the socio-demographic and employment characteristics of respondents who reported using child care, and child care costs were compared. In 2011, parents who reported currently paying for child care (GSS) spent almost $6700 per year ($7,500 for children age 5 and under). According to the tax files, individuals claimed just over $3900 per year ($4,700). Approximately one in four individuals who reported child care costs on the GSS did not report any amount on their tax file; about four in ten who claimed child care on the tax file did not report any cost on the survey. Multivariate analyses suggested that individuals with a lower education, lower income, with Indigenous identity, and who were self-employed were less likely to make a tax claim despite reporting child care expenses on the GSS. Further examination of child care costs by province and by type of care are necessary, as is research to determine the most accurate way to measure and report child care costs.

Mapping the General Social Survey to the Generic Statistical Business Process Model: NORC's Experience

2015 ◽  
Vol 38 (3) ◽  
pp. 21
Author(s):  
Scot Ausborn ◽  
Julia Rotondo ◽  
Tim Mulcahy
Keyword(s):  
Business Process ◽  
Process Model ◽  
General Social Survey ◽  
Business Process Model ◽  
Social Survey

Mapping the General Social Survey to the Generic Statistical Business Process Model: NORC's Experience

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