Restorying Canada: Multiple Narratives in Progress
Bibliographic record
Abstract
This article examines, from two different perspectives, the relationship between historical and literary modes of restorying Canada: first exploring the process by which the country has shaped itself historically since 1867 to become one of the world’s most successful multicultural societies; and second, examining literary and artistic narratives that have had a wide impact on our understanding of what it means to be Canadian, and added a unique layer to our sense of the country’s potential. Basing the analysis on Will Kymlicka’s notion of multiculturalism, and on Jane Urquhart’s fictional text A Number of Things: Stories of Canada Told Through Fifty Objects (2016), as well as on Charlotte’s Gray’s historical essay The Promise of Canada. 150 Years – People and Ideas that Have Shaped Our Country (2016), we argue that the 150th anniversary of the Confederation is an ideal moment to re-examine stories, ideas and notions of identity/diversity, political decisions and transformations that shaped modern Canada. Thus, “restorying Canada” brings about bold challenges to conventions of how we remember, invites critique and inclusive alternative narratives.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.057 | 0.053 |
| Scholarly communication | 0.023 | 0.010 |
| Open science | 0.004 | 0.015 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.007 | 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".