150 years of Canada grappling with diversity since 1867
Bibliographic record
Abstract
On July 1, 2017, Canada celebrated the 150th anniversary of Confederation. The nation-wide festivities prompted ambiguous reactions and contradictory responses since they officially proclaimed to celebrate "what it means to be Canadian." Drawing on the analytical perspectives of Diversity Studies, this fifth volume of the "Diversity / Diversité / Diversität" series explores the repercussions of "Canada 150's" focus on identity. The contributions touch upon issues of Canada's French and English dualism; of its settler colonial past and present and the role of Indigenous Peoples in Canada's identity narrative; of Canada's religious, cultural, ethnic and racial diversity; and of the challenge of forging a "Canadian" identity. The authors analyze these and other problems arising from the tensions between identity and diversity by empirically addressing topics such as multicultural memories, Canadian literary and political discourses, Métis history, Canada's Indigenous peoples, Canada's official federal discourse on language and culture, and Canada's evolving citizenship regimes. Contributors: Marie-Eve Beaulieu, Charles Blattberg, Paul Carls, Sarah Henzi, Jane Jenson, Wolfgang Klooss, Gillian Lane-Mercier, Pierre Lavoie, Ursula Lehmkuhl, Laurence McFalls, Nikolas Schall, Lisa Schaub, Elisabeth Tutschek
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.048 | 0.016 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".