Bibliographic record
Abstract
Three Stoic doctrines have heavily influenced the course of later moral philosophy: (1) Eudaemonism: the ultimate end for rational action is the agent's own happiness. (2) Naturalism: happiness and virtue consist in living in accord with nature. (3) Moralism: moral virtue is to be chosen for its own sake and is to be preferred above any combination of items with non-moral value. These Stoic doctrines provide some later moralists with a starting-point and an outline that they try to develop and amplify. These moralists include supporters of the position that I will call 'Scholastic naturalism'. For other later moralists, Stoicism provides a target; they develop their own positions by explaining why they reject the Stoic position. Still others defend some of these Stoic doctrines and reject others. For obvious reasons, my account of the influence of these Stoic doctrines will be highly selective. I will simply sketch Scholastic naturalism through a few remarks about Aquinas, Suarez, and Grotius. On the other side, I will examine Pufendorf’s reasons for rejecting Scholastic naturalism, and the attempts of Butler and Hutcheson to defend some Stoic doctrines while rejecting others. My interest in these reactions to Stoicism and Scholastic naturalism is primarily philosophical. I hope to understand how different people argue for or against these doctrines, and to see how reasonable the arguments are. It will be clear that I cannot complete this task in this one chapter; I will simply try to identify the main arguments and to raise some relevant questions about them.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.036 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 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".