Judging the Judges: Wittgenstein’s Sceptical Paradox for Debates in the Philosophy of Neuroscience
Bibliographic record
Abstract
In their work, Philosophical Foundations of Neuroscience, Maxwell Bennett and Peter Hacker argue that modern neuroscientists are labouring under a conceptual confusion— that of wrongly ascribing psychological predicates such as “thinks” or “infers” to parts of the brain, instead of to the whole person. They contend that such use of these folk psychology concepts violates the rules of their use. This argument has met with stiff rebuttals from philosophers such as Daniel Dennett and Paul Churchland, who counter that Bennett and Hacker have overstepped the bounds of their ordinary-language analysis in the case of neuroscientific research. These defenders of the current neuroscience project argue that there are no explicit rules available to point out this supposed violation, and until such rules are made available (and shown to be valid), critics such as Bennett and Hacker have no available justification for such claims against the coherence of neuroscientist’s language use. Within the context of this debate, an examination of Ludwig Wittgenstein’s arguments on the subject of language use and rule following will be undertaken, specifically from the perspective of Saul Kripke’s reading of the Philosophical Investigations as the formulation of a unique Wittgensteinian sceptical paradox. Kripke’s reading of Wittgenstein regards numerical privacy and justification is used to provide a possible rebuttal for Bennett and Hacker to their critics in this debate.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.015 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.006 | 0.064 |
| Scholarly communication | 0.010 | 0.023 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.010 | 0.017 |
| Insufficient payload (model declined to judge) | 0.003 | 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".