No exit? Intellectual integrity under the regime of ‘evidence’ and ‘best‐practices’
Bibliographic record
Abstract
No exit? Have we arrived at an impasse in the health sciences? Has the regime of 'evidence', coupled with corporate models of accountability and 'best-practices', led to an inexorable decline in innovation, scholarship, and actual health care? Would it be fair to speak of a 'methodological fundamentalism' from which there is no escape? In this article, we make an argument about intellectual integrity and good faith. We take this risk knowing full well that we do so in a hostile political climate in the health sciences, positioning ourselves against those who quietly but assiduously control the very terms by which the public faithfully understands 'integrity' and 'truth'. In doing so, we offer an honest critique of these definitions and of the systemic power that is reproduced and guarded by the gatekeepers of 'Good Science'.
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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 | 0.240 | 0.302 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.013 | 0.218 |
| Scholarly communication | 0.043 | 0.055 |
| Open science | 0.005 | 0.020 |
| Research integrity | 0.025 | 0.044 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".