Bibliographic record
Abstract
Dossiers spéciaux sur le FMI à la rescousse de l’Argentine, la première année de l’administration Fernando De la Rua, la reprise des négociations en vue de résoudre la question du Chiapas sous le gouvernement de Vicente Fox, le cas Embraer-Bombardier, ainsi que les pourparlers commerciaux entre le Chili et les États-Unis. Pour cette première chronique 2001 et outre la participation plus régulière de Christian Deblock (FMI et brèves hémisphériques), dolbeck@hotmail.com), plusieurs collaborateurs ont nouvellement été mis à contribution : Guilherme de Araujo Silva (Brésil), directeur du programme de la licence en Relations internationales à UniverCidade, Rio de Janeiro, et étudiant au doctorat en relations internationales à l’Université Southern California (USC) (desaraujo@usc.edu) ; Pablo Heidrich (Argentine), doctorant en Économie politique et politiques publiques (PEPP) à USC (heidrich@usc.edu) ; Rodolfo Diaz Sarvide (Chiapas), coordonnateur, Secrétariat de développement social, gouvernement de l’État du Chiapas (sarvide@verdeamerica.zzn.com). Leurs textes ont été traduits dans les sections correspondantes. Mentionnons également que cette chronique "hémisphérique" bénéficie, comme les précédentes, de la collaboration étroite de Claude Despatie à Montréal.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.052 | 0.011 |
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".