Les croisements de l’éthique et des morales entre francophonie et anglophonie à l’âge classique
Bibliographic record
Abstract
During the seventeenth and eighteenth centuries, French authors did not ignore the word “éthique,” but neither did they make it play a specific role in their works like they did with “morale,” their preferred term. By contrast, English writers were more likely than their counterparts to distinguish “Ethicks” from “Morals.” Consequently, it is mainly in English-language writings that the separation of the two terms can be found. The key authors invested in refining these distinctions are Locke, Shaftesbury, Hutcheson, Hume, and Bentham—the last one being the philosopher who enacted the splitting of these two terms. From their meditations gradually emerges a belief in the conditions for a common moral platform and position; in those authors’ estimation, this foundation could properly take the place of mathematical ethical inquiry. Among those exposing utilitarianism, ethics are a matter of calculation, ethical action achievable through mathematical rules. If calculation is still limited with Hutcheson, it becomes subtler still with Bentham, even if the first utilitarian author stays within the parameters of this moral philosophy. Bentham seems to be inspired by Bayesian–Pricean probability calculus, and his main and seminal ideas are developed in “The Axioms of Pathology” at the end of the “Pannomial Fragments.”
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.018 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".