Intelligence artificielle, solidarité et assurances en Europe et au Canada: Feuille de route pour une coopération internationale
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Plusieurs membres de l'OBVIA ont participé à l'élaboration du rapport "Intelligence artificielle, solidarité et assurances en Europe et au Canada", qui propose des principes structurants et de bonnes pratiques en lien avec l'IA pour les acteurs du secteur des assurances. Il a été coordonnée par des institutions indépendantes à but non lucratif (la Human Technology Foundation et son réseau OPTIC) en collaboration avec des partenaires canadiens et français. Les membres de l'OBVIA impliqués dans les travaux sont Marc-Antoine Dilhac, William Sanger, Francois Laviolette, Réjean Roy, Nathalie de Marcellis et Lyse Langlois.
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.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 it