Review of <i>One West, Two Myths II: Essays on Comparison</i> Edited by C. L. Higham and Robert Thacker
Bibliographic record
Abstract
With this collection, editors C. L. Higham and Robert Thacker aim to define the parameters and potential of the Canada-U.S. comparative Wests field of study, with particular reference to its myths. The American Review of Canadian Studies (winter 2003) originally published the main body of essays, but this republication has important additions. New appendices include Frederick Jackson Turner's 1893 essay on "The Significance of the Frontier in American History" and J. M. S. Careless's 1954 essay on "Frontierism, Metropolitanism, and Canadian History." Both are useful for understanding what R. Douglas Frances in a separate essay states as the persistent "difficulty of getting beyond and supplanting" the influence of Turner and Harold Adams Innis on u.S.-Canada West history. A third appendix presents Higham's thoughts on the most important works in the field, new and classic, and its major problems, especially the symbiotic relationship between comparative, transnational, and borderlands histories. New features, "Questions to Ponder" and "Must Reads," emphasize the conversations the editors wish to deepen. This edition has fewer illustrations than the special issue of ARCS, but includes new maps; especially useful are visualizations of the Canadian Theory of Metropolitanism and the American Frontier Thesis. Individual essays point to ways the field of comparative North American Wests could advance beyond its emergent status. Frances suggests new depth might be found in uncovering a "multiplicity of myths" shaped by diverse western peoples, while William H. Katerberg clarifies a northern element that distinguishes both Canadian national and western myths from those of the U.S. Sarah Carter argues that the "gendered dimensions" of mythic "social and cultural constructs" and "nation building" need complex consideration. Her essay explores how different national policies played out in the lives of Aboriginal and white women. Great Plains Quarterly readers will be pleased that many of the theories and queries about comparative Wests are discussed with reference to the states and provinces of its region of focus. Readers will be interested especially in David L. Williams's discussion of the French history of the transnational northern grasslands.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.013 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".