Bibliographic record
Abstract
Pleasure and displeasure have been suffering from intellectual neglect in the philosophy of mind. In contemporary work, the mode of experience which effectively dominates discussion is vision—David Marr's work on visual representation and L. Weiskrantz's work on blindsight are familiar to many philosophers of mind, as are the philosophical uses of such work, and no one seems to tire of working out what the frog's eye tells the frog's brain. Who, though, can name a leading theorist of pain? As a source of examples and intuitions, pain is a perennial favorite in ethics and the philosophy of mind, but in both disciplines pain is taken for granted far more often than it is the object of analysis. Equally significantly, forms of displeasure other than pains are very largely neglected. Pleasure, for its part, has been the nigh-exclusive province of moral theorists; few other than Strawson seem to have taken a special interest in it in the philosophy of mind. The object of the present work is to rectify this neglect, and to give an account of pleasure and displeasure which reveals a striking degree of unity and theoretical tractability underlying the diverse phenomena: arepresentationalistaccount.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.059 |
| Scholarly communication | 0.010 | 0.015 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".