Narratives of power: historical mythologies in contemporary Québec and Canada
Bibliographic record
Abstract
The official narratives that Canada tells itself about its history and identity facilitate the contemporary exercise of power, determining who is to be regarded as fully belonging and who is alien. While race is excised from these national narratives, it has in fact been central to the formation of Canadian nationhood. The image of the respectable, peaceful, multiculturalism-loving Canadian citizen, descendant of the two founding nations, France and Britain, goes hand in hand with its opposites: the Indigenous ‘Indian’, the Black, the immigrant newcomer and the refugee. This article examines the historical and contemporary variants of these images and the narratives constructed around them, arguing that Canada’s history of colonial violence, slavery and racism has been marginalised through their circulation, and that their continued invocation in public debates on crime, terrorism and immigration is a crucial factor in the perpetuation of racial exclusion. The particular ways in which Québec has conceived its relationship to English Canada add an interesting dimension to this discussion: in the 1960s, Quebecers saw in the political struggles of Africans and African Americans a metaphor for their own identity. But Québec’s own version of a founding national narrative is a tale of innocence and victimhood that conveniently omits the colonisation of Indigenous peoples, the practice of slavery and racial exclusion.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.061 | 0.051 |
| Scholarly communication | 0.019 | 0.007 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".