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Understanding Science with Large Language Models?
Potentials for the History, Philosophy, and Sociology of Science- Editors:
- | | |
- Series:
- Science Studies
- Publisher:
- 2026
Summary
How are large language models (LLMs) changing research in the history, philosophy, and sociology of science (HPSS)? The contributors to this volume show how these tools open new possibilities for interpretative scholarship while posing fresh challenges for fields that thrive on qualitative methods, nuance, and historical depth. In essays, dialogues, and provocations, they capture a field in motion at a pivotal moment, driven by the rise of AI. These insights speak not only to HPSS scholars but also to readers across the humanities, social sciences, and AI-related fields, positioning HPSS as a bridge for understanding and shaping how LLMs enter research and society.
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Bibliographic data
- Edition
- 1/2026
- Copyright Year
- 2026
- ISBN-Print
- 978-3-8376-7994-6
- ISBN-Online
- 978-3-8394-4752-9
- Publisher
- transcript, Bielefeld
- Series
- Science Studies
- Volume
- 0
- Language
- English
- Pages
- 523
- Product Type
- Edited Book
Table of contents
ChapterPages
- Critical concerns for using LLMs in the (computational) humanities and beyondPages 35 - 50Authors:Download chapter (PDF)
- On the use and limitations of large language models in historical scholarshipPages 71 - 99Authors: |Download chapter (PDF)
- Encoded humanities, or: not everything has to be generativePages 101 - 114Authors: |Download chapter (PDF)
- Why pursue temporally‐grounded AI for historical disciplines, and what makes it so challenging?Pages 127 - 141Authors:Download chapter (PDF)
- Zero‐shot generation of synthetic historical data with LLMsPages 151 - 177Authors: | | | |Download chapter (PDF)
- LLMs and multilingual historical corpora in a digital history projectPages 179 - 187Authors:Download chapter (PDF)
- Computational conceptual history of scientific conceptsPages 197 - 215Authors: |Download chapter (PDF)
- Exploring disciplinary differences in semantic uniformityPages 243 - 256Authors:Download chapter (PDF)
- Use of large language models in the classification of scientific texts into disciplinesPages 257 - 270Authors: | | |Download chapter (PDF)
- Discursive parallels of the chemical revolutionPages 271 - 290Authors: | | |Download chapter (PDF)
- The potential of LLMs for constructing a socio‐legal knowledge graphPages 293 - 305Authors:Download chapter (PDF)
- Large language models in interdisciplinary research settingsPages 335 - 342Authors: | |Download chapter (PDF)
- Co‑creation of AI technology, empowering curators of cultural heritage information and guarding research commonsPages 383 - 412Authors: | | | | |Download chapter (PDF)
- AI‑Reporter: a path to a new genre of scientific communicationPages 413 - 438Authors:Download chapter (PDF)
- Supporting citation context analysis with large language models raises questions that should have been asked 40 years agoPages 453 - 469Authors: |Download chapter (PDF)
- Reconstructive citation context analysis using large language modelsPages 471 - 492Authors: | |Download chapter (PDF)





