Interdependencies A Comparative Study of National Mythologies and Multiculturalism in the United States and Canada
Bibliographic record
Abstract
Both the United States and Canada are immigrant countries whose national mythologies and national identities have been the subject of much discussion - albeit for different reasons. Whereas the United States is famous for its various national myths and its strong national identity, Canada has for a long time been known for the contrary. Unlike their southern neighbors, Canadians were said to lack a common mythology and have for a long time struggled to define their national identity. Nevertheless, myths have played a decisive role in the construction of both national narratives. This book comparatively analyzes how national myths like the American Dream or the Canadian myth of survival have not only shaped the two profoundly different national identities but also the two unique multicultural ideals commonly known as the American melting pot and the Canadian multicultural mosaic. Individual national myths existing in the United States and Canada are investigated with a focus on their respective interdependencies with the two countries' approaches to their multiculturality. This book thus both juxtaposes the two North American mythologies and provides new insights into the interrelations of national myths and multiculturalism, answering questions such as »How has American exceptionalism contributed to the ideal of e pluribus unum?« or »How does Canada's myth of North relate to the country's self-image as a multicultural nation?«
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.029 | 0.018 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".