Bibliographic record
Abstract
NATURALISM REDIVIVUS I have argued that the ancient philosophers generally treated knowledge and belief naturalistically. The non-naturalistic or criteriological approach of the Standard Analysis is aborted in Plato's Theaetetus , although the Standard Analysis itself lives on in its subsequent application to rational belief. If knowledge is a natural feature of human life like digestion or pregnancy, it would seem to be available for empirical scientific investigation. If that is so, ancient epistemological naturalism will find itself at a disadvantage, to put it mildly. For to admit the relevance of biology, neurophysiology, psychology and so on to the study of epistemology seems to ensure that ancient naturalism is doomed to melt into the deep background of historical curiosities. In this light, if one rejects a contemporary version of naturalised epistemology, the only plausible alternative would seem to be some non-naturalised approach, most appropriately rooted in logical or linguistic analysis and in the evaluative use of a certain class of terms and concepts. An analysis of how our words or concepts are used or even how they ought to be used need not have anything to fear from the deliverances of modern empirical science. By contrast, insofar as ancient epistemology is supposed to be dependent on ancient science, its subsequent obsolescence appears to be inevitable. I have in the preceding chapters tried to cast some doubt both on the supposition that ancient epistemological naturalism is susceptible to refutation by the claims of empirical science and on the perhaps more egregious error of supposing that ancient epistemology is not a form of naturalism.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.025 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".