Semantic Pragmatism and A Priori Knawledge (or ‘Yes we could all be brains in a vat’)
Bibliographic record
Abstract
Hilary Putnam has famously argued that we can know that we are not brains in a vat because the hypothesis that we are is self-refuting. While Putnam's argument has generated interest primarily as a novel response to skepticism, he originally introduced his brain in a vat scenario to help illustrate a point about the ‘mind/world relationship.’ In particular, he intended it to be part of an argument against the coherence of metaphysical realism, and thus to be part of a defense of his conception of truth as idealized rational acceptability. Putnam's discussion has already inspired a substantial body of criticism, but it will be argued here that these criticisms fail to capture the central problem with his argument. Indeed, it will be shown that, rather than simply following from his semantic externalism, Putnam's conclusions about the self-refuting character of the brain in a vat hypothesis are actually out of line with central and plausible aspects of his own account of the relationship between our minds and the world.
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 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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".