chile_2023_social-welfare-survey_oo

92,031 responses from 11,234 respondents to 17 items.

One of 11 tables from the same source; this one measures CASEN Work Occupation. The others are listed under Related tables.

About this table

DescriptionChile CASEN work/occupation questions
LicenceCC BY 4.0
Source datahttps://bidat.gob.cl/details/ficha/dataset/f80237f5-9231-40d1-a1f1-ed93751dc2ac

Size and shape

Responses92,031
Respondents11,234
Items17
Response categories5
Responses per respondent8.192
Responses per item5413.588
Density0.482
LongitudinalTRUE

Classification

age rangeMixed
sampleInternet-based, Representative
construct typeOpinion/attitude
measurement toolSurvey/questionnaire
item formatMixed
primary language(s)spa
construct nameCASEN Work Occupation

Item text

This table has item text in the IRW: the wording administered to respondents, not just the response codes.

InstrumentChile CASEN work/occupation questions
Mean words per item11.354
Mean characters per item61.031
Mean characters per response11.551
Flesch-Kincaid grade level4.001

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, chile_2023_social-welfare-survey.do. 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.

ColumnWhat it isSource column
IRW standard columns
dateIRW standard Calendar time in seconds — either seconds elapsed since data collection start (relative) or Unix time (absolute).unixtime
idIRW 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
itemIRW standard Item identifier.made in the build script
respIRW standard Response value.`var'
Respondent covariates
cov_age_rangeCovariate tramoebs2
cov_genderCovariate sg02

What item codes and covariate values stand for is in the source’s codebook, Libro_de_codigos_EBS_2023.xlsx, and its questionnaire, Cuestionario_EBS_2023_241001.pdf, which shows the item wording.

Get the data

Download CSVno account neededBrowse on Redivisexplore and queryCroissant metadataHugging Face, Kaggle, OpenML

Or load it directly in R or Python:

# R (no account needed)
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("chile_2023_social-welfare-survey_oo")
# Python (needs a free Redivis account)
pip install irw

import irw
df = irw.fetch("chile_2023_social-welfare-survey_oo")

How to cite

@misc{bidat_dataset_2023,
  title = {Dataset from BiDAT},
  url = {https://bidat.gob.cl/details/ficha/dataset/f80237f5-9231-40d1-a1f1-ed93751dc2ac},
  year = {2023},
  note = {Accessed: 2023-10-01}
}

Version and provenance

IRW versionv540
Redivis datasetitem_response_warehouse_2 v33.0
Redivis dataset DOI10.57761/6m04-m698
Manifest pin for this IRW versionv33.0
Metadata sourceirw_meta v37.0