Bibliographic record
Abstract
There is widespread scholarly disagreement concerning Hume's use and understanding of the term "moral distinctions." While commentators offer a range of interpretations of this term, there has been little attempt to understand the diverse range of meanings attributed to it, or to adjudicate between them. The present paper attempts to contribute to the understanding of Hume's position on the nature and origin of moral distinctions by filling this lacuna. I argue that Hume uses "moral distinctions" in two senses. First, in the context of his refutation of the moral rationalist position on moral distinctions, Hume uses "moral distinctions" to refer to the demonstrable, eternal, and necessary relations that obtain between, and apparently exist separately from, moral qualities. And second, in the context of his account of the role that sentiment plays in moral perception, Hume uses "moral distinctions" to refer to the differences that we uniformly experience when evaluating an object, between qualities that are both distinctively moral and the strict opposites of one another. For example, the difference between moral good and evil, or the distinction between particular virtues and vices, such as the difference between justice and injustice, or between gratitude and ingratitude, and the like. Hume explains the uniformity in the way we experience and talk about moral distinctions, by locating their origin in the same sentiment or impression that, in his understanding, explains how we perceive and, consequently, have ideas of moral qualities themselves. This enables Hume not just to replace the rationalist's moral epistemology, but also to reject Hobbesian skepticism about "the reality of moral distinctions" (EPM 1.2; SBN 169–70), despite arguing that "moral distinctions" does not represent anything external to the mind.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.018 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".