Digital Humanities in the TIME-US Project: Richness and Contribution of Interdisciplinary Methods for Labour History
Résumé
This chapter explores the interdisciplinary approach of the TIME-US project, which aims to reconstruct the working conditions of men and women in the French textile industry from the seventeenth to the twentieth century. Faced with sparse and heterogeneous historical data—particularly on women’s work—TIME-US combines methods from labour history, digital humanities, and natural language processing (NLP) to transform qualitative archival sources into structured, analyzable data. Drawing on the concept of “datafication,” the project builds a richly annotated corpus of digitized documents, processed using OCR, handwritten text recognition, and semantic annotation pipelines. It demonstrates how computational methods, including the “verb-oriented method,” enable the identification of work-related activities in large text corpora. The article highlights the methodological innovations and collaborative practices between historians and computer scientists that made this possible. TIME-US contributes not only to labour history by making invisible work more visible but also to digital humanities by showcasing blended reading approaches that combine distant and close reading. It advocates for historians' active involvement in the design of digital tools to ensure meaningful, critically-informed research.
| Origine | Fichiers produits par l'(les) auteur(s) |
|---|---|
| Licence |