Bibliographic record
Abstract
De Pierris has argued that Hume is what she calls an inductivist about the proper method of scientific inquiry: science proceeds by formulating inductively-established empirical generalizations that subsume an increasing number of observable phenomena in their scope. De Pierris thus limits Hume's understanding of scientific inquiry, including his own science of human nature, to observable phenomena. By contrast, I argue that Hume's conception of science allows for the positing of, and belief in, unobservable theoretical entities on purely explanatory grounds. I present the details of De Pierris's interpretation of Hume, and the reasons and means for rejecting it. I then consider Hume's explicit statements on his science of human nature to show that all of these are compatible with Hume's accepting a more expansive understanding of scientific explanation. Finally, I briefly consider some examples from the Treatise of Hume's employing just such a methodology.
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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 | 0.000 | 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 | 0.001 |
| 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".