Bibliographic record
Abstract
If the 1970s were marked by the policy on multiculturalism adopted by Pierre Trudeau, the Quebec question was approached with caution against a backdrop of claims for the sovereignty of this province. This question did not only concern domestic politics, but also arose on the international level, Quebec having been associated, for example, with the beginnings of the organization of Francophonie after the treaty of Niamey (20 March 1970). The objective of this contribution is to analyze the way in which Brian Mulroney himself perceived this positioning of Canada in the Francophonie to avoid on the one hand the delegitimization of the multiculturalist policy initiated in the 1970s and recognize on the other hand the cultural specificity of the province of Quebec. Based on the study of Brian Mulroney’s memoirs and on methodologies from discourse analysis, the findings show that the author has an ethos of reconciliation, concerned with finding a Canadian identity deeply attached to the Commonwealth and the Francophonie. This ethos is antithetical to that of Pierre Trudeau, whose political and diplomatic actions are judged negatively by Brian Mulroney. Positioning on the Francophone question is at the heart of this fundamental disagreement, which at the same time explains Brian Mulroney’s new diplomatic action in favor of a more political Francophonie and in favor of new constitutional agreements to correct Pierre Trudeau’s conception of multiculturalism.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.012 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| 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".