Published on 25 April 2023 |

Version 20230425

WISCO occupations_ISCO08_5dgt_55languages_4000titles_with_mapping_surveycodings_20230425

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Tijdens, Kea

Description

Occupation is a key variable in socio-economic research, used in a wide variety of studies, but its measurement is a major challenge. The national stocks of job titles are large with 10,000’s of job titles, they are unstructured with vague boundaries between job titles, and the stock has no fixed list but instead many entries and exits over time. Measuring occupations in a multi-country survey is even a larger challenge, because occupations with the same tasks have to be coded similarly across countries. Most surveys use an open-ended survey question to measure occupations. The challenge relates to time-consuming and expensive office-coding. Alternatively, web surveys and CAPI surveys allow using a look-up database with occupational titles. The Surveycodings team and WageIndicator Foundation provide a multilingual database of coded and translated occupational titles that allow for urvey respondents' self-identification of their occupational titles, thereby tackling the challenge for multi-country surveys to classify job titles into ISCO-08 classification of occupations and to do so consistently across countries. The database is gradually extended with more occupational titles and more languages. The current version, as of 20230202, holds 55 languages for at most 4,000 titles, though some languages have only half of the titles translated, among others because the occupations do not exist in the country at stake or because no translations were aavailable. Details about this and related databases as well as related publications can be found at https://www.surveycodings.org/articles/codings/occupation.

Citations (0)

Mentions (0)

Metrics

Dataset Index

1.8

FAIR Score

73%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

Zenodo

Assigned Domain

Subfield

Statistics and Probability

Field

Mathematics

Domain

Physical Sciences

Confidence Score

42%

Source

Scholar Data Model

Keywords

occupations, ISCO classification, surveys, measurement, multilingual, multicountry

Normalization Factors

FT

13.46

CTw

1.00

MTw

1.00