Seeking common ground / Trouver un terrain d'entente: politics of national parks establishment in the Torngat Mountains, Arctic Canada
Bibliographic record
Abstract
Establishing national parks is not an innocent “conservation” practice; it is, fundamentally, a culturally defined, political one, and one that reflects the distribution of power within human societies. The present thesis proposes to approach the study of national park establishment in multinational Canada from the perspective of political geography. I look at national park establishment in northern Canada with special attention to the interactions between politics and territory, and how both interact with culture in the creation of a collective identity. I base my observations on a case study from the Torngat Mountains, in Nunavik and Nunatsiavut, and I show that provincial and federal national parks in Québec and Canada serve an array of purposes beyond the sole intention of protecting the environment. My analysis shows that Canadian parks are imbued with societal values that contribute to their establishment as an intercultural space, and symbols of Canadian unity and identity. In contrast, Québec's parks are not valued as an intercultural space, but as a geopolitical tool that protects and proclaims the province's territorial integrity and national status. I emphasize the link between national parks and cultural issues by comparing them with similar institutions: national museums. The Canadian Museum of Civilization in Ottawa and the “Musée de la civilisation” in Québec city clearly expose Canada's and Québec's cultural politics. National parks – or at least some of them – appear as one component of the cultural politics of different communities of Canada, one that supports competing and/or converging nationalist projects at the regional, provincial and federal levels of administration. In the long run, the new and future national parks of the Torngat Mountains might affect the integrity of Québec's territory, or that of Inuit cultural identity.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.030 | 0.009 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".