G. Matthew Adkins. The Idea of the Sciences in the French Enlightenment: A Reinterpretation.
Bibliographic record
Abstract
G. Matthew Adkins probably derived the title of his book from Leonard M. Marsak's Bernard de Fontenelle: The Idea of Science in the French Enlightenment (1959). Despite the promised broad scope, this brief study concerns three principal characters: Samuel Sorbière, Bernard le Bovier de Fontenelle, and Marie-Jean-Antoine-Nicolas Caritat, marquis de Condorcet. Sorbière, in a 1663 discourse to the philosophical circle of Henri-Louis Habert de Montmor, aspired to found an academy of sciences. When the king accepted such plans three years later, Sorbière was not involved. Fontenelle and Condorcet were both secrétaires perpétuels of the Paris Royal Academy of Sciences, and thus spokesmen for the role of the sciences in society. Voltaire and Anne-Robert-Jacques Turgot also appear in strong supporting roles. Within those limits, Adkins provides a fresh intellectual history of the idea of cultivation of the sciences (really of natural philosophy) as it relates to individual virtue and political rationality. It is hardly, however, a reinterpretation of the significance of the sciences in the French Enlightenment.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.016 | 0.006 |
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".