This paper introduces OccCANINE, an open-source tool that maps occupational descriptions to HISCO codes. Manual coding is slow and error-prone; OccCANINE replaces weeks of work with results in minutes. We fine-tune CANINE on 15.8 million description-code pairs from 29 sources in 13 languages. The model achieves 96 percent accuracy, precision, and recall. We also show that the approach generalizes to three systems - OCC1950, OCCICEM, and ISCO-68 - and release them open source. By breaking the "HISCO barrier," OccCANINE democratizes access to high-quality occupational coding, enabling broader research in economics, economic history, and related disciplines.
Cite
@article{arxiv.2402.13604,
title = {Breaking the HISCO Barrier: Automatic Occupational Standardization with OccCANINE},
author = {Christian Møller Dahl and Torben Johansen and Christian Vedel},
journal= {arXiv preprint arXiv:2402.13604},
year = {2026}
}
Comments
All code and guides on how to use OccCANINE is available on GitHub https://github.com/christianvedels/OccCANINE