Re-evaluating the Principle of Virtuous Motives: Abilities, Justice, and the Concept of Natural Virtue
Bibliographic record
Abstract
Abstract: Hume claims in the Treatise that all virtuous actions derive their moral merit only from virtuous motives. Many scholars regard this statement as a universal axiom in Hume's moral theory, and others read it as applying to all natural or non-artificial virtues. This paper challenges both of these readings. It argues that Hume does not endorse this statement universally since many virtuous qualities in his catalogue are not characterized by motives, and that he does not need to endorse it given his conception of character and theory of moral sentiment. Moreover, many qualities not characterized by motives can also be classified as natural, according to the distinction between natural and artificial virtues offered in part 3, Book 3 of the Treatise . Finally, I propose some alternative interpretations of the proper scope and function of this principle of virtuous motives.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".