Contested Histories of Racialization and the Legacies of Sir John A Macdonald
Bibliographic record
Abstract
The year 2015 marked the bicentenary of Sir John A. Macdonald’s birth and sparked renewed interest in his legacies and the contested histories of race and racialization in Canada. One version of a monolithic history of Canada venerates Sir John A. Macdonald for his role as Canada’s first Prime Minister, a paternal figure of Confederation, and a nation builder who implemented projects of infrastructure and industrial development (i.e., Canadian Pacific Railway) and systems of land tenure and ownership. This dominating story of Macdonald’s legacies reflects a historical canon of biographies, dramatic plays, musicals, guided tours and monuments such that Macdonald’s history is conflated with a founding history of Canada. By contrast, diverse and different stories about human erasure, physical and cultural displacement, and assimilation—notably, of Black, Asian, and Indigenous peoples—are made marginal by the dominating discourse of so-called Canadian national progress. The essays presented in this issue of the Journal of Critical Race Inquiry (JCRI) (Volume 3, Number 1) contest dominant interpretations of the legacies of Sir John A. Macdonald by offering theoretical, performative, and experiential analyses of Canadian history, race, colonialism, and Indigenous cultural resurgence.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.048 | 0.052 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.007 |
| 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".