Bibliographic record
Abstract
Abstract It is a well-worn platitude that knowledge excludes luck. According to anti-luck virtue epistemology, making good on the anti-luck platitude requires an explicit anti-luck condition along the lines of safety : S knows that p only if S’s true belief that p could not have easily been mistaken. This paper offers an independent, virtue epistemological argument against the claim that safety is a necessary condition of knowledge, one that adequately captures the anti-luck platitude. The argument proceeds by way of analogy. I focus on two paradigmatic kinds of normative achievements that also exclude luck: (i) – having a doxastically justified belief and (ii) – performing a morally worthy action. I then show that while (i) and (ii) exclude luck, they are nevertheless susceptible to what I call “modal luck.” I then move on to show that knowledge, or at least some instance of knowledge, is a normative achievement, which I claim provides strong reasons to expect that knowledge is also susceptible to modal luck. Since safety entails that knowledge is incompatible with modal luck, the argument provides strong reasons to reject safety as a necessary condition of knowledge.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.048 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".