Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This study utilizes data from the General Social Survey (GSS), a nationally representative, repeated cross-sectional survey administered by NORC at the University of Chicago. The GSS is one of the most authoritative sources of longitudinal public opinion data in the United States, tracking American attitudes, beliefs, and behaviors across a wide range of social, political, and economic domains since 1972.
For the purposes of this analysis, the dataset was restricted to survey waves from 2000 to 2022, to capture contemporary patterns of polarization around economic redistribution and party identity, particularly during the post-9/11 and post-2016 political realignments. Data were accessed and downloaded through the GSS Data Explorer (https://gssdataexplorer.norc.org/), using the platform’s variable filtering and trend tools.
Key variables used in the analysis include:
Dependent variable: Support for redistribution, measured by agreement with the statement “The government should reduce income differences between the rich and the poor.”
Independent variables:
Party identification (Democrat, Republican, Independent/Other)
Racial resentment indicators, including agreement with items such as “Blacks should work their way up without special favors”
Year (centered for interaction and trend modeling)
Demographic controls: age, gender, income, education, and geographic region
The analytic sample includes respondents with valid responses to all core variables, totaling 5,483 observations after listwise deletion and multiple imputation for missing attitudinal items. All analyses were conducted using R and Python, with appropriate statistical methods for logistic regression, rolling OLS estimation, and interaction modeling. Attempts to estimate a Markov Switching model encountered convergence issues and are excluded from the final analysis.
The GSS sampling design includes multistage area probability sampling and post-stratification weights to ensure representativeness of the U.S. adult population. All interpretations in this study are based on weighted data unless otherwise noted.
Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
License information was derived automatically
This report contains the field data obtained during the February to April 1960 oceanographic expedition of the USC&GS ship Explorer, together with such results from the analyses of these data as are completed to date. As additional studies are completed, the results will be published by the U.S. Coast and Geodetic Survey or by the other Government agencies, private oceanographic institutions, or individual scientists who are primarily concerned. The USC&GSS Explorer is a 1,900-ton, 220-foot Ocean Survey Ship (OSS 28). During the winter of 1960, the ship was scheduled for a routine transfer from her original home port of Seattle, Wash., to be based in the future out of Norfolk, Va. With the current accelerated demand for oceanographic information, it was felt that this transfer offered a unique opportunity to obtain useful oceanographic information along the route from Seattle to Norfolk.
Not seeing a result you expected?
Learn how you can add new datasets to our index.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This study utilizes data from the General Social Survey (GSS), a nationally representative, repeated cross-sectional survey administered by NORC at the University of Chicago. The GSS is one of the most authoritative sources of longitudinal public opinion data in the United States, tracking American attitudes, beliefs, and behaviors across a wide range of social, political, and economic domains since 1972.
For the purposes of this analysis, the dataset was restricted to survey waves from 2000 to 2022, to capture contemporary patterns of polarization around economic redistribution and party identity, particularly during the post-9/11 and post-2016 political realignments. Data were accessed and downloaded through the GSS Data Explorer (https://gssdataexplorer.norc.org/), using the platform’s variable filtering and trend tools.
Key variables used in the analysis include:
Dependent variable: Support for redistribution, measured by agreement with the statement “The government should reduce income differences between the rich and the poor.”
Independent variables:
Party identification (Democrat, Republican, Independent/Other)
Racial resentment indicators, including agreement with items such as “Blacks should work their way up without special favors”
Year (centered for interaction and trend modeling)
Demographic controls: age, gender, income, education, and geographic region
The analytic sample includes respondents with valid responses to all core variables, totaling 5,483 observations after listwise deletion and multiple imputation for missing attitudinal items. All analyses were conducted using R and Python, with appropriate statistical methods for logistic regression, rolling OLS estimation, and interaction modeling. Attempts to estimate a Markov Switching model encountered convergence issues and are excluded from the final analysis.
The GSS sampling design includes multistage area probability sampling and post-stratification weights to ensure representativeness of the U.S. adult population. All interpretations in this study are based on weighted data unless otherwise noted.