7,227 responses from 803 respondents to 9 items.
One of 4 tables from the same source; this one is the bits_s2 table. The others are listed under Related tables.
| Description | Polish Bern Illegitimate Tasks Scale (BITS, 9 items, 5-point) completed by 803 employees in Poland (sample 2, 2020). |
|---|---|
| Reference | Basinska, B. A., & Dåderman, A. M. (2023). Psychometric properties of the Bern illegitimate tasks scale using classical test and item response theories. Scientific Reports, 13, 7211. https://doi.org/10.1038/s41598-023-34006-0 |
| DOI | 10.1038/s41598-023-34006-0 |
| Licence | CC BY 4.0 |
| Source data | https://data.mendeley.com/datasets/7wfgz62xgs/1 |
| Responses | 7,227 |
|---|---|
| Respondents | 803 |
| Items | 9 |
| Response categories | 5 |
| Responses per respondent | 9 |
| Responses per item | 803 |
| Density | 1 |
| Longitudinal | FALSE |
| sample | Workplace |
|---|---|
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | pol |
This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, basinska_2023_bits.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 | FII_Age |
cov_children | Covariate 0 = nie · 1 = tak | FII_Kids |
cov_city_size | Covariate 1 = aglomeracja miejska lub miasto powyżej 100 tys. mieszkańców · 2 = miasto poniżej 100 tys. mieszkańców · 3 = wieś | FII_City |
cov_education | Covariate 1 = zasadnicze zawodowe · 2 = średnie · 3 = wyższe licencjat / inż. · 4 = wyższe mgr / mgr inż. · 5 = doktorat | FII_Edu |
cov_gender | Covariate 0 = Kobieta · 1 = Mężczyzna | FII_Gender |
cov_manager | Covariate 0 = nie · 1 = tak | FII_Manger |
cov_occupation | Covariate 1 = Nauczyciel · 2 = Pielęgniarka/Pielęgniarz · 3 = Sektor IT (programista, informatyk, administrator sieci komputerowych) · 4 = Urzędnik administracji publicznej | FII_Occupation |
cov_org_size | Covariate | FII_sizeOrg |
cov_partnered | Covariate 0 = woln%a% · 1 = w związku partnerskim/małżeńskim | FII_Marriage |
cov_province | Covariate 16 labelled values1 = Dolnośląskie · 2 = Kujawsko-Pomorskie · 3 = Lubelskie · 4 = Lubuskie · 5 = Łódzkie · 6 = Małopolskie · 7 = Mazowieckie · 8 = Opolskie · 9 = Podkarpackie · 10 = Podlaskie · 11 = Pomorskie · 12 = Śląskie · 13 = Świętokrzyskie · 14 = Warmińsko-Mazurskie · 15 = Wielkopolskie · 16 = Zachodniopomorskie | FII_Province |
cov_tenure | Covariate | FII_Tenure |
cov_tenure_org | Covariate | FII_tenureOrg |
Covariate value labels are the source’s own, as the IRW recorded them. What item codes and any unlabelled 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("basinska_2023_bits_s2")
# Python
pip install irw
import irw
df = irw.fetch("basinska_2023_bits_s2")
@article{Basinska_2023, title={Psychometric properties of the Bern illegitimate tasks scale using classical test and item response theories}, volume={13}, ISSN={2045-2322}, url={http://dx.doi.org/10.1038/s41598-023-34006-0}, DOI={10.1038/s41598-023-34006-0}, number={1}, journal={Scientific Reports}, publisher={Springer Science and Business Media LLC}, author={Basinska, Beata Aleksandra and Dåderman, Anna Maria}, year={2023}, month=May }
| IRW version | v549 |
|---|---|
| Redivis dataset | item_response_warehouse_6 v5.10 |
| Redivis dataset DOI | 10.57761/8zbf-t397 |
| Manifest pin for this IRW version | v5.10 |
| Metadata source | irw_meta v39.0 |