Bibliographic record
Abstract
Maurice Daumas (1910-1984) est un fondateur, mais dont on a désappris le nom. Conservateur au Conservatoire national des Arts & Métiers à Paris, puis titulaire de la première Chaire d’histoire des techniques, il a dirigé la monumentaleHistoire générale des techniques(PUF, 1968-1979). C’est lui qui a fait entrer le patrimoine industriel dans le champ académique français en fondant la revueL’Archéologie industrielle en Franceet en publiant en 1980 un livre qui porte le même titre. Dans ce livre, Daumas évoque, notamment, les très riches heures de l’histoire industrielle de la région stéphanoise. Suite à la découverte récente des archives de l’enquête nationale qu’il a conduite sur plusieurs années pour documenter son livre, nous proposons d’étudier la manière dont il a abordé l’héritage industriel stéphanois, en mettant à jour la méthodologie qu’il a utilisée et les réseaux locaux sur lesquels il s’est appuyé.In fine, il s’agit d’observer la naissance d’un champ de recherche en France et en Europe : l’archéologie industrielle.
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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".