Bibliographic record
Abstract
The current IASP definition of pain has come under renewed criticisms recently. There is a new momentum for its revision as reflected by the fact that IASP has now a Presidential Task Force dedicated to look into whether there is enough warrant to update the definition. I critically review all the major criticisms of the current definition in detail, and raise new difficulties rarely discussed before. I show that none of the major criticisms has enough warrant to force us to substantially revise the current definition. Combined with the discussion of the new difficulties, there is nonetheless a need to restate the definition using slightly different terminology that will make the original intent of the current definition clearer and more precise. A restatement of the definition is proposed and its potential is discussed in light of some empirical questions that remain.
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 | 0.049 | 0.088 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.003 | 0.019 |
| Scholarly communication | 0.010 | 0.019 |
| Open science | 0.008 | 0.006 |
| Research integrity | 0.008 | 0.028 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".