La lutte contre l’exclusion numérique et la revitalisation des collectivités locales
Bibliographic record
Abstract
Ce texte aborde le problème de la lutte contre l’exclusion numérique en lien avec la revitalisation des communautés locales dans le contexte de la nouvelle économie où les réseaux ont une place fondamentale. Nous savons que l’accès à l’information est devenu un facteur d’intensification des inégalités sociales et territoriales, mais sous le leadership des acteurs locaux et communautaires, il peut aussi devenir une base pour le renforcement des communautés et pour la lutte contre la pauvreté et l’exclusion. C’est ce que montre le cas du Carrefour d’éducation populaire de Pointe-Saint-Charles, à l’oeuvre dans l’un des quartiers les plus défavorisés de Montréal. Cet organisme renforce l’empowerment collectif en combinant la solidarité numérique aux autres actions collectives visant l’amélioration des conditions de vie des citoyens et la revitalisation de la communauté.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".