Bibliographic record
Abstract
Prominent in the volume as in the history is the character created for the upper Athabasca River watershed by virtue of its having formed part of a reserved area.For a century now, the valley and its tributaries have been managed by various federal government units, first the Department of the Interior (1907-1911), then, beginning in 1911, its Dominion Parks Branch, followed by today's Parks Canada/Parcs Canada department.Although beginning as private concerns, the railways in the upper Athabasca became another government enterprise, Canadian National Railways, by the third decade of the twentieth century.Before it and government, another institution, the Hudson's Bay Company (the early nineteenth-century world's largest company in terms of geographical domination) controlled much of the human activity in the Athabasca.Culturing Wilderness aims to treat the full two centuries of that institutional history as well as to provide profiles of several key individuals: studies of the fur trade, governance, tourism, railway publicity for the park, alpinism, and the general human influence on non-human nature are complemented by essays about the painter-traveller Paul Kane's depictions of the valley, homesteading by Harkin seems to tap into the appeal that mountains had held for European cultures since the eighteenth century.Succinctly observant, Rebecca Stolnit has remarked that "English and many other languages associate altitude, ascent, and height with power, virtue, and status."16Harkin capitalized on that status in his early years as commissioner; that is, he turned wilderness into capital.Former city editor of the Ottawa Journal before becoming the political and private secretary of Liberal cabinet minister Sir Clifford Sifton, he understood how to promote parks to the country's governors.Harkin is famous-or notorious-for costing out the price of mountain scenery and its contribution to the government's coffers.He spearheaded the cause of parks by promoting the economic value of their scenery.17 Even when he had amenities built for tourists of more modest means, such as automobile campers, Harkin sacrificed wilderness to tourism.As Taylor notes, only much later in the century, in the 1960s, did park officials voice their concern that fully serviced campgrounds, with automatic washing machines, electric stoves, and the like, were "gradually destroying the whole concept of camping."During Harkin's era, both rail and road changed the way in which the Jasper area was used as a thoroughfare.With the advent of rail service
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.394 | 0.192 |
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".