Stephen Harper et l’Afrique : ignorance, désintérêt, compassion ou le business avant tout ?
Bibliographic record
Abstract
Notre contribution a pour objectif de dresser le bilan des neuf années de Stephen Harper au pouvoir, du point de vue des relations entre le Canada et les pays d’Afrique subsaharienne, en ce qui concerne notamment les liens diplomatiques, l’aide au développement et les positions politiques sur les enjeux internationaux. Nous cherchons à mettre en exergue la manière dont Harper est parvenu à déconstruire et reconstruire la place du Canada en Afrique. Cette transformation de la présence canadienne s’est faite à partir de nouvelles orientations axées, moins sur la recherche du prestige à tout prix ou du rayonnement, mais plus sur des considérations technocratiques et donc davantage arrimées aux intérêts canadiens. Les valeurs sous-tendant l’approche du gouvernement Harper vis-à-vis du continent africain sont : la compassion pour les pays les plus pauvres et l’utilitarisme économique au profit des mieux lotis.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.029 | 0.029 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".