Bibliographic record
Abstract
A flourishing democracy should have a great deal of space for a wide range of beliefs and practices.The issue of vaccine hesitancy requires that we have as much data and information as possible in order to determine the precise point at which those beliefs and practices may endanger others or the population as a whole.Imposing restrictions before determining that point is about power rather than protection, and ultimately alienates portions of the population. RésuméUne démocratie saine doit prévoir suffisamment d' espace pour une vaste gamme de croyances et de pratiques.La question de la réticence à la vaccination demande que nous ayons en main toutes les données possibles afin de déterminer le point précis où ces croyances et pratiques peuvent mettre en danger des individus ou l' ensemble de la population.Imposer des restrictions avant de connaître ce point est plus une question de pouvoir que de protection et, en bout de ligne, peut aliéner des segments de la population.T
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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 | 0.019 | 0.086 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.010 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.009 | 0.004 |
| Research integrity | 0.181 | 0.112 |
| Insufficient payload (model declined to judge) | 0.012 | 0.014 |
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".