From "Snow Eagle" to "Ban the Tan:" Aviation and Canadian Climatic Identity
Bibliographic record
Abstract
Candidate in History of Science, Technology, and Medicine at the University of Oklahoma.Her dissertation examines how aviation, especially air travel, was a site in which Canadians negotiated modernity and nationalism, especially the aspects of nationalism tied to climate and geography.Her work has appeared in Technology and Culture, the Journal for the History of Astronomy, and an upcoming edited volume on Science, Technology, and the Modern in Canada.She was born and raised in Ottawa, Canada and misses the winters terribly.1 "What Others Think of Us-Warm-Blooded."Between Ourselves January 1953, 3 2 North Stars were used by TCA, Canadian Pacific Airways, and the Royal Canadian Air Force.The British Overseas Airways Corporation bought a few, but they were not widely used.From "Snow Eagle" to "Ban the Tan" -Stein April 2017Aviation has been a key technology in Euro-Canadian self-fashioning, largely due to the nation's size and seemingly impenetrable North.3 Marionne Cronin, Stephen Bocking, and Jonathan Vance have all shown how Canada's Arctic was made legible to the state by aerial surveying.Jeanne Haffner's work on city planning also suggests that the airplane, or at least aerial view, could stand in for social order.4 The relative ease with which aviation knitted together distances was especially resonant in Canada, since Canada's size was (and still is) both a point of national pride and a perceived barrier to mobility.Furthermore, everyday exposure to aviation, especially during and after the Second World War, was shaped by state actors who built a discourse of nature, technology, and nation in which airplanes were positioned to both highlight and transcend Canadian geography.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.032 | 0.017 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".