A4 Refereed article in a conference publication
Measuring Social Integration Through Participation: Categorizing Organizations and Leisure Activities in the Displaced Karelians Interview Archive using LLMs; 
Authors: Laato, Joonatan; Schroderus, Veera; Kanerva, Jenna; Kauppi, Jenni; Lummaa, Virpi; Ginter, Filip
Editors: Alves, Diego; Bizzoni, Yuri; Degaetano-Ortlieb, Stefania; Kazantseva, Anna; Pagel, Janis; Szpakowicz, Stan
Conference name: SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature
Publisher: Association for Computational Linguistics
Publication year: 2026
Book title : Proceedings of the 10th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature 2026
First page : 111
Last page: 127
ISBN: 979-8-89176-373-9
DOI: https://doi.org/10.18653/v1/2026.latechclfl-1.11
Publication's open availability at the time of reporting: Open Access
Publication channel's open availability : Open Access publication channel
Web address : https://doi.org/10.18653/v1/2026.latechclfl-1.11
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/527004670
Self-archived copy's licence: CC BY
Self-archived copy's version: Publisher`s PDF
Digitized historical archives make it possible to study everyday social life on a large scale, but the information extracted directly from text often does not directly allow one to answer the research questions posed by historians or sociologists in a quantitative manner. We address this problem in a large collection of Finnish World War II Karelian evacuee family interviews. Prior work extracted more than 350K mentions of leisure time activities and organizational memberships from these interviews, yielding 71K unique activity and organization names—far too many to analyze directly. We develop a categorization framework that captures key aspects of participation (the kind of activity/organization, how social it typically is, how regularly it happens, and how physically demanding it is). We annotate a gold-standard set to allow for a reliable evaluation, and then test whether large language models can apply the same schema at scale. Using a simple voting approach across multiple model runs, we find that an open-weight LLM can closely match expert judgments. Finally, we apply the method to label the 350K entities, producing a structured resource for downstream studies of social integration and related outcomes.
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