Hume’s Theory of Moral Judgment in Light of His Explanatory Project
Bibliographic record
Abstract
Abstract: In this paper, I argue that Hume’s account of moral judgment is best understood if it is read in light of Hume’s explanatory project. I first lay out the textual support to show that Hume’s account of justice in the Treatise includes both approval of a motive that gives rise to the virtue of justice, and approval of a system of conduct, irrespective of a motive. I then argue that we can allow for such plurality in Hume’s theory of moral judgment if we view it in light of his explanatory project: finding unifying causes for disparate phenomena. Hume offers a unified theory of moral judgment because he can show that the different approvals are explained by the same causes. Finally, I argue that viewing Hume’s account of moral judgment in light of his explanatory project allows us to appreciate a further distinction between the moral judgment of the natural and the artificial virtues: while judgments of the former are fully explained by the causes of a certain motive, the latter are only fully explained by the causes of the motive in the context of a convention, which in turn is partially constituted by non-approved 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".