467 responses from 437 respondents to 3 items.
| Description | Ratings of benevolence trait for nominated targets. |
|---|---|
| Reference | Sun, J., Wu, W., & Goodwin, G. P. (2025). Are moral people happier? Answers from reputation-based measures of moral character. Journal of Personality and Social Psychology, 128(5), 1160–1180. |
| DOI | 10.1037/pspp0000539 |
| Licence | CC BY 4.0 |
| Source data | https://osf.io/5e9y3/overview |
| Responses | 467 |
|---|---|
| Respondents | 437 |
| Items | 3 |
| Response categories | 5 |
| Responses per respondent | 1.069 |
| Responses per item | 155.667 |
| Density | 0.356 |
| Longitudinal | FALSE |
| age range | Mixed |
|---|---|
| sample | Internet-based, Targeted/specific |
| construct type | Opinion/attitude |
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | eng |
| construct name | Benevolence |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Ratings of benevolence trait for nominated targets. |
|---|---|
| Mean words per item | 4.714 |
| Mean characters per item | 28.643 |
| Mean characters per response | 13.143 |
| Flesch-Kincaid grade level | 5.200 |
cov_moralgroupcov_nidcov_tididitemresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("sun_2025_morality_study3_benevolence")
# Python
pip install irw
import irw
df = irw.fetch("sun_2025_morality_study3_benevolence")
| IRW version | v393 |
|---|---|
| Redivis dataset | item_response_warehouse_2 v19.0 |
| Redivis dataset DOI | 10.57761/qtx5-4m80 |
| Manifest pin for this IRW version | v19.0 |
| Metadata source | irw_meta v23.0 |