Building Capacity for Sustainable Development: The Canada-Brazil Bilateral Cooperation Projects with SENAI
Bibliographic record
Abstract
ABSTRACT The cooperation between Brazil and Canada in support of projects with the National Service for Industrial Apprenticeship (SENAI) has been seen in both countries as a history of successes. The paper describes the Canadian supported projects developed and implemented at SENAI, and considers the many lessons learned from over twenty years of cooperation. Both the process of learning and the strategic application of the lessons learned have contributed to the success of the projects. It is hoped that they can also contribute to the development of new projects at SENAI, in Brazil, and to Canadian supported projects elsewhere. RÉSUMÉ Le Brésil et le Canada s'accordent à dire que la coopération dont les deux pays ont fait preuve dans l'appui aux projets du Service national d'apprentissage industriel (SENAI) a donné d'excellents résultats. Cet article décrit les projets élaborés et mis en place par le SENAI, avec l'aide du Canada, et se penche sur les nombreuses leçons apprises au cours de ces vingt années de cooperation. Lé succès remportipaé les différentes initiatives est dû à la fois au processus même d'apprentissage et à la mise en application stratégique des leçons apprises. Il est à espérer que ces expériences contribueront également à l'élaboration de nouveaux projets par le SENAI au Brésil, et aux projets semblables ailleurs dans le monde qui sont appuyés par le Canada.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".