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Automatic methods for coding historical occupation descriptions to standard classifications

Research output: Contribution to conferencePaperpeer-review

Abstract

The increasing availability of digitised registration records presents a significant opportunity for research in many fields including those of human geography, genealogy and medicine. Re-examining original records allows researchers to study relationships between factors such as occupation, cause of death, illness, and geographic region. This can be facilitated by coding these factors to standard classifications. This paper describes work to develop a method for automatically coding the occupations from 29 million Scottish birth, death and marriage records, containing around 50 million occupation descriptions, to standard classifications. A range of approaches using text processing and supervised machine learning is evaluated, achieving accuracy of 92.3 ± 0.2% on a smaller test set. The paper speculates on further development that may be needed for classification of the full data set.
Original languageEnglish
Publication statusAccepted/In press - 2014
EventWorkshop on Population Reconstruction - International Institute of Social History, Amsterdam, Netherlands
Duration: 19 Feb 201421 Feb 2014

Workshop

WorkshopWorkshop on Population Reconstruction
Country/TerritoryNetherlands
CityAmsterdam
Period19/02/1421/02/14

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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