Mapping North America: Comparative North American Literature and Its Contexts
Bibliographic record
Abstract
Introduction IN 1980, CANADIAN WRITER George Bowering published Burning Water , a novel about Captain George Vancouver's 1792 voyage and search for the Northwest Passage. The story begins as a “vision, com[ing] out of the far fog” (2007, 5) and materializes as the British explorers’ ships arrive on the coast of the Northwest Pacific. The characters begin to obsessively chart and name all rivers, islands, and inlets, not knowing what it is exactly that they concoct on their maps. As the narrator explains, “they followed the shoreline because what else was there? Especially with the clouds and rain and sometimes fog, and all the time the riptide and all the islands, what else was there? They followed the shoreline of the continent, if that was what it was, and the shoreline was seldom a question of north and south; it went through every degree on the compass. How it got eventually and generally north was difficult to see, or often so” (Bowering 2007, 103). This is how the author imagines the journey to have taken place, an exploration with imprecise objectives and an unknown outcome through an unnamed territory hidden behind fog. The nebulous continent reveals an outline with a rugged shore rather than clean-cut edges; any inlets that promise to lead far into the interior often end up as small streams. Although a general location, north, may be discernible, to fully make sense of the land, the explorers need to go in all directions. Nevertheless, the historical George Vancouver, unlike his fictional counterpart, returned to Britain and created maps that would long remain among the most accurate of the Pacific coast. Let us take George Vancouver's voyage as a starting point for discussing Comparative North American Literature. Although its central subject, “North America,” is blurry at best, American Studies and Canadian Studies have become solid disciplines to chart the territory and create maps for navigating through the respective national literatures. A Comparative North American Studies approach does not proclaim the nation an insignificant category for investigation but accounts for cultural and social differences between the United States and Canada. The merit of this comparative approach lies in addressing the ways in which the two nations differ but are nonetheless connected in a North American context.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.029 |
| Science and technology studies | 0.024 | 0.028 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".