1er Café de bioéthique « Le citoyen et ses objets connectés : qu’advient-il de ses données? »
Bibliographic record
Abstract
Ce compte-rendu résume les échanges tenus lors du 1er Café de bioéthique de 2019, qui a porté sur le thème : « Le citoyen et ses objets connectés : qu’advient-il de ses données? » Trois experts panélistes et un public de 70 personnes ont participé à cette rencontre. La discussion a notamment précisé les avantages que peuvent avoir les objets connectés, tels qu’une autonomisation et une responsabilisation des individus, mais a aussi mis en lumière certains risques comme une hypernormativité ou encore la question d’obtention d’un consentement valide. Des pistes de solution et de réglementation ont été proposées par le public et les experts. Cette rencontre s’inscrit dans une série de trois Cafés de bioéthique tenue à Montréal et à Québec sur le sujet de l’éthique, de la santé et des données.
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 | 0.064 | 0.080 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.020 | 0.025 |
| Scholarly communication | 0.017 | 0.010 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.007 | 0.014 |
| Insufficient payload (model declined to judge) | 0.020 | 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; 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".