2,847 responses from 410 respondents to 7 items.
| Description | Motivation to participate in agricultural citizen science, 7 items (contributing, pastime, sharing, expectation, expert interaction, community interaction, helping), 1-5; N = 410 farmers in India, Ethiopia and Honduras; cov_country, cov_household_head, cov_age, cov_sex, cov_education. |
|---|---|
| Reference | Beza, E., Steinke, J., van Etten, J., Reidsma, P., Fadda, C., Mittra, S., Mathur, P., & Kooistra, L. (2017). What are the prospects for citizen science in agriculture? Evidence from three continents on motivation and mobile telephone use of resource-poor farmers. PLOS ONE, 12(5), e0175700. https://doi.org/10.1371/journal.pone.0175700 |
| DOI | 10.1371/journal.pone.0175700 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.5061/dryad.v51bv |
| Responses | 2,847 |
|---|---|
| Respondents | 410 |
| Items | 7 |
| Response categories | 5 |
| Responses per respondent | 6.944 |
| Responses per item | 406.714 |
| Density | 0.992 |
| Longitudinal | FALSE |
| age range | Adult (18+) |
|---|---|
| sample | Targeted/specific |
| construct type | Opinion/attitude |
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | hin, amh, spa |
| construct name | Motivation to participate in citizen science |
This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, beza_2017_citizen_science.py. 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). | made in the build script |
item | IRW standard Item identifier. | made in the build script |
resp | IRW standard Response value. | made in the build script |
| Respondent covariates | ||
cov_age | Covariate | Age(in years) |
cov_country | Covariate | Country |
cov_education | Covariate | Education Level |
cov_household_head | Covariate | HHHead(1Yes2No) |
cov_sex | Covariate | Sex(1M2F) |
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("beza_2017_motivation")
# Python
pip install irw
import irw
df = irw.fetch("beza_2017_motivation")
@article{Beza_2017, title={What are the prospects for citizen science in agriculture? Evidence from three continents on motivation and mobile telephone use of resource-poor farmers}, volume={12}, ISSN={1932-6203}, url={http://dx.doi.org/10.1371/journal.pone.0175700}, DOI={10.1371/journal.pone.0175700}, number={5}, journal={PLOS ONE}, publisher={Public Library of Science (PLoS)}, author={Beza, Eskender and Steinke, Jonathan and van Etten, Jacob and Reidsma, Pytrik and Fadda, Carlo and Mittra, Sarika and Mathur, Prem and Kooistra, Lammert}, editor={Rossiter, D G}, year={2017}, month=May, pages={e0175700} }
| 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 |