Bibliographic record
Abstract
« Nous avons ici une des présentations faites à l’occasion des \nconférences annuelles Chevrette-Marx, consacrées soit aux principes \nfondamentaux, soit au fédéralisme ou encore aux libertés publiques. \nLe titre de l’ouvrage de Danielle Pinard, Les faits alternatifs \ndu droit constitutionnel, nous amène à penser aux interventions devant \nles médias de Kellyanne Conway, conseillère de l’actuel président \ndes États-Unis. L’auteure y fait allusion pour expliquer que ce \nsont là des éléments faisant appel à l’émotion et à des opinions personnelles \nplutôt qu’à des faits vérifiables. Elle se pose ainsi les questions \nsuivantes : Les faits sur lesquels les lois s’appuient souvent \nsont-ils véridiques? Les conclusions que les législateurs tirent de \n« faits » pourraient-elles n’être que de simples approximations? […] »
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads 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".