Bibliographic record
Abstract
Cet article expose les resultats d’une enquete menee en 2008 aupres de 389 adherents a douze reseaux d’echange de proximite (REP) quebecois. Apres avoir presente ces REP dans leurs dimensions organisationnelle et institutionnelle et decrit le profil de leurs membres, les auteurs montrent, donnees statistiques a l’appui, en quoi la condition socioeconomique des adherents vient moduler le lien d’usage entretenu avec le reseau. En effet, si les REP quebecois accueillent une diversite de personnes et repondent a des attentes multiples, notre analyse revele que le genre, l’âge, la scolarite et le niveau de revenu des adherents sont associes, sur le plan statistique, aux motifs d’adhesion, a l’appreciation du REP et aux retombees percues. On constate aussi que plus fort est l’engagement des adherents dans leur REP, plus grandes sont la satisfaction a son egard et les incidences qu’on lui attribue.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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 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".