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Breaking the HISCO Barrier: Automatic Occupational Standardization with OccCANINE

Author

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  • Christian Møller Dahl

    (University of Southern Denmark)

  • Torben Johansen

    (University of Southern Denmark)

  • Christian Vedel

    (University of Southern Denmark)

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.

Suggested Citation

  • Christian Møller Dahl & Torben Johansen & Christian Vedel, 2024. "Breaking the HISCO Barrier: Automatic Occupational Standardization with OccCANINE," Working Papers 0255, European Historical Economics Society (EHES).
    • Handle: RePEc:hes:wpaper:0255
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    File URL: https://www.ehes.org/wp/EHES_255.pdf
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    References listed on IDEAS

    as
    1. Allen,Robert C., 2009. "The British Industrial Revolution in Global Perspective," Cambridge Books, Cambridge University Press, number 9780521868273.
    2. Berger, Thor, 2019. "Railroads and Rural Industrialization: evidence from a Historical Policy Experiment," Explorations in Economic History, Elsevier, vol. 74(C).
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    Cited by:

    1. Jeanet Sinding Bentzen & Nina Boberg-Fazlić & Paul Sharp & Christian Volmar Skovsgaard & Christian Vedel, 2024. "Assimilate for God: The Impact of Religious Divisions on Danish American Communities," Working Papers 0253, European Historical Economics Society (EHES).

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    More about this item

    Keywords

    Occupational Standardization; HISCO Classification System; Machine Learning in Economic History; Language Models;
    All these keywords.

    JEL classification:

    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • J1 - Labor and Demographic Economics - - Demographic Economics
    • N01 - Economic History - - General - - - Development of the Discipline: Historiographical; Sources and Methods
    • N3 - Economic History - - Labor and Consumers, Demography, Education, Health, Welfare, Income, Wealth, Religion, and Philanthropy
    • N6 - Economic History - - Manufacturing and Construction
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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