[Lingtyp] 2nd call for papers: Linguistic data and language comparison in light of the 'quantitative turn' and 'big data' - a workshop and symposium

[Sandra Auderset]

—— 2nd call for submissions —— apologies for cross-posting

Linguistic data and language comparison in light of the ‘quantitative turn’ and ‘big data’ – a workshop and symposium

May 7 to 9 2025 at the Department of Linguistics, University of Bern
Organizer and contact: Sandra Auderset (sandra.auderset at unibe.ch)

Timeline
Application submissions due: November 15, 2024 (midnight CEST)
Notifications sent out by: December 20, 2024
Workshop: May 7 to 9, 2025

Full call with all information: https://www.isw.unibe.ch/forschung/workshops/linguistic_data_and_language_comparison/index_ger.html

This workshop provides a forum for in-depth discussion and exchange on theoretical and methodological issues related to linguistic data and language comparison by exploring the relationship of data gathering, analysis, and annotation practices in linguistics in light of the 'quantitative turn' and the advent of ‘big data’. A particular focus lies on synchronic and diachronic comparison and the role of understudied/endangered languages. Potential talk and discussion topics include but are not limited to:
types of linguistic data and their relationship to qualitative and quantitative analyses
transparency and reproducibility in the context of primary and secondary data
the role of understudied and endangered languages in methodological and theoretical advancements
biases in annotation and analysis of linguistic data and how they can be addressed or mitigated
the connection of quantitative/computational methods and language documentation, especially how they can mutually benefit each other
models and methodologies for bottom-up language comparison
database design principles and their effect on linguistic theorizing
best practices’ for quantitative and statistical methods drawing on a diverse set of data
models of collaboration between researchers focusing on different aspects of data management and analysis (e.g. recordings and annotation, statistical modeling, questionnaire development)

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