Le Sud... Et le Nord dans la mondialisation: Quelles alternatives ?
Bibliographic record
Abstract
Sous la direction du titulaire de la CRDC, Louis Favreau en collaboration avec A.Salam Fall (RIPESS) et Gerald Larose (GESQ), douze auteurs, lies a la CRDC, a des organisations de developpement du Sud et a des unive rsites (en Afrique et en Amerique latine), ont collabore a la production de ce cahier en vue de la Conference internationale intitule Le SUD...et le NORD dans la mondialisation : quelles alternatives?, conference qui s’est tenue a l’Universite du Quebec en Outaouais les 24 et 25 septembre 2003. Nous visions la participation de 300 personnes. Pres de 450 personnes en provenance de tout le Quebec s’y sont inscrites, des invites internationaux de 15 pays dont 12 du Sud et pres de 40 organisations (organisations de cooperation internationale, cooperatives, groupes de femmes, organisations syndicales, agences de developpement local de toute categorie (CDEC, CDR...) de meme que des intervenants et decideurs du secteur public) y ont participe. Ces contributions Nord-Sud soumises au quotidien Le Devoir a permis la realisation d’un cahier special de six pages dans ce journal la fin de semaine des 13 et 14 septembre avec l’intitule «Altermondialisation, democratie et developpement». A l’exception du dernier texte (non reproduit faute d’espace), les articles soumis par la CRDC ont paru dans le journal. Nous reproduisons ici la version originale de ces textes.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.010 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 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".