Bibliographic record
Abstract
In the direct realist tradition of Reid and Austin, disjunctivism has joined its precursors in proudly trumpeting its allegiance with naïve realism. And the theory gains plausibility, particularly as compared with adverbialism, if one considers a Wittgensteinian line of argument regarding the use of sensation words. But ‘no common factor’ doctrines can be shown to be inconsistent with the naïve realism that has served as their main support. This does not mean that either disjunctivism or the Wittgensteinian perspective on language acquisition that informed it must be false. It does indicate, however, that linguistic arguments against private or internal meanings do not imply perceptual directness and that the espousal of direct realism—naïve or not—does not require adherence to disjunctivism.
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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 | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.050 |
| Scholarly communication | 0.007 | 0.014 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.012 |
| Insufficient payload (model declined to judge) | 0.006 | 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".