« Tuer le père ». Un exemple d'approche psycho-sociologique de la filiation mathématique de Gaspard Monge
Bibliographic record
Abstract
Jérôme Laurentin, «Killing the Father»: a Tentative Psycho Sociological Approach to the Mathematicians who Succeeded Gaspard Monge. The interdisciplinarity sought by the workshop was fostered by a number of historians and sociologists specialising in the sciences. However, it is full of pitfalls which arouse passions and trigger dissension, exacerbated more often than not by the fear of compromising scientific authority. Mindful of these apprehensions, I would nonetheless wish to go beyond a strictly internal survey of the work of Gaspard Monge's pupils, with a view to seeking in their relationships with the master, in the changes made to teaching practice, in a family romance disrupted by the Revolution, the rationale for a style and the choice of a whole range of mathematical research topics. This approach focusses on Michel- Ange Lancret and Charles- Julien Brianchon, two of the students most closely associated with Gaspard Monge by historical tradition. The manner in which they called into question his teaching will be highlighted and may help demonstrate that a study confined to their scientific treatises cannot fully account for the existence of an intellectual school. Some sociological and psychological indicators are briefly addressed, based on their own accounts and their scientific treatises, using the modern tools of scientometrics, in order to show that methodological relativism has a significant contribution to make, in the history of mathematics as well.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".