Bibliographic record
Abstract
Maurice Daumas (1910-1984) was a founder, but whose name is now forgotten. He was a curator at the Conservatoire national des Arts & Métiers (Paris), then holder of the first Chair in the history of techniques, and he directed the monumentalHistoire générale des techniques. It was him who brought industrial heritage into the French academic field by founding the journalL’Archéologie industrielle en Franceand by publishing in 1980 a book with the same title. In this book, Daumas evokes in particular the glorious timesof industrial history in the Saint-Étienne region. Following the recent discovery of the archives of the national survey that he conducted over several years to document his book, I propose to examine the way in which he approached the industrial heritage of Saint-Étienne, the first French industrial city for a long time, by updating the methodology he used and the local networks on which it relied. In sum, this contribution is about the birth of a field of research in France and in Europe: industrial archeology.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.007 | 0.016 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".