The Mapping of Center and Periphery, and the Geography of Otherness
Bibliographic record
Abstract
Some literatures, like Canadian literature, may be considered minor because Canada is not a major power. But in reality, Canadian literature and other literatures, large or small, are part of a cultural history that is not merely local or even national, but international. The territories of culture and literature in literal or metaphorical terms shift over time. Using a comparative method, this article examines texts—such as The Saga of Eric the Red and works by Columbus, Verrazzano, Jeannette C. Armstrong, Marie Annharte Baker and Carrie Best—to demonstrate the shifting boundaries of time and space and to explore the connections between cultures and literatures in Canada, Europe and the Atlantic and international worlds as part of a longstanding globalization. The article demonstrates that the hybridity resulting from cross-cultural contact and colonization typically blurs the distinction between center and periphery, revealing the historical fluidity of the political boundaries on which the concepts of national and world literatures are based. In doing so, it focuses on how North America, particularly Canada, and the historical process of its discovery, settlement, and colonization have connected this region to other parts of the world.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.012 | 0.035 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".