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Breaking the HISCO Barrier: Automatic Occupational Standardization with OccCANINE

Authors :
Dahl, Christian Møller
Johansen, Torben
Vedel, Christian
Publication Year :
2024

Abstract

This paper introduces a new tool, OccCANINE, to automatically transform occupational descriptions into the HISCO classification system. The manual work involved in processing and classifying occupational descriptions is error-prone, tedious, and time-consuming. We finetune a preexisting language model (CANINE) to do this automatically, thereby performing in seconds and minutes what previously took days and weeks. The model is trained on 14 million pairs of occupational descriptions and HISCO codes in 13 different languages contributed by 22 different sources. Our approach is shown to have accuracy, recall, and precision above 90 percent. Our tool breaks the metaphorical HISCO barrier and makes this data readily available for analysis of occupational structures with broad applicability in economics, economic history, and various related disciplines.<br />Comment: All code and guides on how to use OccCANINE is available on GitHub https://github.com/christianvedels/OccCANINE

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2402.13604
Document Type :
Working Paper