Consentez-vous (toujours) à participer à ma recherche ?
Bibliographic record
Abstract
Au Québec et au Canada, pour qu’une personne participe à une recherche, il faut qu’elle y consente formellement, le plus souvent, par la signature d’un « formulaire de consentement ». Mais comment parvient-on à obtenir le consentement de personnes vulnérables ? Par « vulnérabilité », nous parlons de personnes éprouvées de diverses façons, atteintes ou non de maladie, mais souffrant dans leur vie et dans leur société. Participer peut mener à une première prise de conscience de sa propre situation : violence conjugale, fragilité, maladie, déficits, etc. Participer, c’est confier les aspects les plus difficiles ou intimes de sa vie, ou « livrer son corps » à des inconnus, pour leur recherche. Comment s’y prend-t-on alors pour leur demander d’y consentir ? Est-ce délicat, difficile, gênant ? Quels en sont les défis, les ratés, les succès ? Le but principal de ce colloque est de partager les expériences vécues sur le terrain, de discuter des obstacles et d’échanger sur les pistes de solutions possibles.
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 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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.024 | 0.012 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.048 | 0.006 |
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".