Identités ethnoculturelles et politique étrangère : le cas de la politique française du Canada
Bibliographic record
Abstract
Résumé. Cet article propose, grâce à la notion de culture stratégique, une articulation du lien entre identité et politique étrangère. Il met plus particulièrement l'accent sur les effets des identités ethnoculturelles (anglophone et francophone) sur la politique de sécurité internationale du Canada, et soutient l'hypothèse qu'il en résulte une culture stratégique atlantiste et biculturelle, laquelle accorde une importance particulière à la France (de même qu'à la Grande-Bretagne et aux États-Unis). Il ressort de l'analyse historique de celle-ci que la centralité des identités ethnoculturelles canadiennes permet de mieux comprendre l'importance particulière dont jouit la France sur les limites normatives du multilatéralisme et de la légitimité de recourir à la force militaire par le Canada. Abstract. This article seeks to provide a constructivist account of Canadian foreign policy, linking identity and policy, through the concept of strategic culture. It focuses on Canada's dual ethnocultural identities (Anglophone and Francophone) and the bicultural and Atlanticist strategic culture that stems from it. It argues that this strategic culture helps explain France's significant importance (together with the United Kingdom and the United States) in defining the normative boundaries of Canada's multilateralism and legitimacy to use of military force abroad.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.018 | 0.015 |
| Scholarly communication | 0.011 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".