8,048 responses from 1,006 respondents to 8 items.
One of 4 tables from the same source; this one measures Trust in the American citizenry. The others are listed under Related tables.
| Description | Trust in the American citizenry, 8 items, 1-5, after a polarization-perception experiment; N = 1,006 US adults (online, 2020); treat (polarization article vs control), cov_condition, cov_age, cov_gender, cov_income, cov_education, cov_ideology, cov_race, cov_donation_condition. |
|---|---|
| Reference | Lee, A. H.-Y. (2022). Social Trust in Polarized Times: How Perceptions of Political Polarization Affect Americans' Trust in Each Other. Political Behavior. https://doi.org/10.1007/s11109-022-09787-1 |
| DOI | 10.1007/s11109-022-09787-1 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/WXOYVM |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Responses | 8,048 |
|---|---|
| Respondents | 1,006 |
| Items | 8 |
| Response categories | 5 |
| Responses per respondent | 8 |
| Responses per item | 1,006 |
| Density | 1 |
| Longitudinal | FALSE |
| age range | Adult (18+) |
|---|---|
| sample | Internet-based |
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | eng |
| construct name | Trust in the American citizenry |
This codebook is reconstructed by the IRW from the IRW data standard. It is our best reading, not the source’s own codebook, and it may contain mistakes. Where the two disagree, the source data are the authority. If you find an error, please tell us.
| Column | What it is | Source column |
|---|---|---|
| IRW standard columns | ||
id | IRW standard Identifier for the focal unit being measured — typically a person, but sometimes another entity (e.g., a word in a lexical task). | not traced |
item | IRW standard Item identifier. | not traced |
resp | IRW standard Response value. | not traced |
treat | IRW standard Treatment group assignment in experimental studies. | not traced |
| Respondent covariates | ||
cov_age | Covariate | not traced |
cov_condition | Covariate | not traced |
cov_donation_condition | Covariate | not traced |
cov_education | Covariate | not traced |
cov_gender | Covariate | not traced |
cov_ideology | Covariate | not traced |
cov_income | Covariate | not traced |
cov_race | Covariate | not traced |
What item codes and covariate values stand for is in the codebook released with the source data.
Or load it directly in R or Python (both need a free Redivis account; the first call opens a browser to sign in):
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("lee_2022_ameritrust")
# Python
pip install irw
import irw
df = irw.fetch("lee_2022_ameritrust")
@article{Lee_2022, title={Social Trust in Polarized Times: How Perceptions of Political Polarization Affect Americans’ Trust in Each Other}, volume={44}, ISSN={1573-6687}, url={http://dx.doi.org/10.1007/s11109-022-09787-1}, DOI={10.1007/s11109-022-09787-1}, number={3}, journal={Political Behavior}, publisher={Springer Science and Business Media LLC}, author={Lee, Amber Hye-Yon}, year={2022}, month=Mar, pages={1533–1554} }
| IRW version | v584 |
|---|---|
| Redivis dataset | item_response_warehouse_5 v8.5 |
| Redivis dataset DOI | 10.57761/41xy-5k56 |
| Manifest pin for this IRW version | v8.5 |
| Metadata source | irw_meta v44.0 |