Bibliographic record
Abstract
This article examines Canadian cultural nationalism since Confederation through the lens of settler colonial theory, engaging with questions arising from this exercise. Along the way it discusses how settler colonial theory meshes with other theoretical perspectives, particularly nationalism theory. The main body of the paper is a historical overview of how settler cultural production colonized Indigenous peoples symbolically from the mid-nineteenth to the mid-twentieth century. Appropriation from and stereotyping of Indigenous peoples are analyzed. While these forms of indirect erasure were common, a direct erasure that simply ignored the Indigenous fact was far more prevalent. Nationalist cultural producers focused instead on Eurocivility, settler colonizations of other settlers, and Canada’s dual imperia. Moreover, settler colonialism was not the only form of colonialism influencing cultural nationalism: extractive colonialism affected it as well. Settler cultural discourse changed dramatically in the late twentieth century. Radical shifts in the realpolitik of settler-Indigenous relations and settler morality delegitimized erasure practices. Some cultural producers responded by integrating Indigenous peoples into new formulations of national identity, while others popularized representations of settler guilt. The article concludes with observations on the historicity of these new perspectives and how Canada’s legacy of cultural nationalism might constructively inform decolonization.
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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 | 0.004 |
| Science and technology studies | 0.021 | 0.022 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".