Instrumentalization of National Identity in Canada’s Official Languages: Chrétien, Harper and Trudeau
Bibliographic record
Abstract
Abstract Liberal and Conservative federal governments engage in nation-building within official languages governance, seeking to align social and political norms with partisan principles. This article compares the Chrétien, Harper and Justin Trudeau governments’ instrumentalization of Canadian identity in the five action plans and roadmaps for official languages developed since 2003. These documents are comprehensive five-year outlines of the governments’ approach to official languages, interspersed with priorities, funding commitments and minister statements. This analysis is facilitated by a novel interpretive framework, drawing attention to the use of a national narrative, values and affect. Our analysis reveals the Chrétien government to have translated the Liberal, civics-based depiction of Canadian identity to suit an international focus. The Harper government portrayed Canadian identity as true to settler roots, rebuking the Liberal model. Finally, the Trudeau government established a pluralist Canadian narrative to justify Liberal civics as a means for protecting and promoting equity and diversity.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.030 | 0.036 |
| Scholarly communication | 0.016 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".