A clarification on the Boorse–Wakefield debate about health: Is the theoretical/therapeutic distinction dispensable?
Bibliographic record
Abstract
Abstract Although Boorse’s and Wakefield’s accounts of health are generally regarded as competing ones, they are in fact so only if they are aimed at the same concept. Some remarks made by Boorse and Wakefield, however, leave it unclear whether they are. On one possible interpretation, Boorse’s account aims at analysing a theoreticalconcept of abnormality, which ought to be distinguished from a more clinicalor therapeuticconcept, whereas Wakefield’s account aims at analysing a clinicalor therapeuticconcept. The debate between Boorse and Wakefield would then either be merely terminological, or would boil down to whether Boorse is correct to assert the existence of a theoreticalconcept of abnormality which ought to be distinguished from a clinicalor therapeuticone. This paper aims to clarify what is at stake between Boorse and Wakefield, by maintaining that their accounts are most plausibly interpreted as both being aimed towards a theoreticalconcept of abnormality.
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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 | 0.026 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.008 | 0.100 |
| Scholarly communication | 0.010 | 0.023 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.015 | 0.018 |
| Insufficient payload (model declined to judge) | 0.007 | 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".