Bibliographic record
Abstract
Recent scholarship on Samuel Hearne's A Journey to the Northern Ocean (1795) has highlighted how Hearne's journey of exploration functioned to demonstrate the Hudson's Bay Company's strategic geopolitical worth, obscure the violence of its colonialist enterprise, and generate images of an empty North conducive to colonial settlement. Drawing on such scholarship, this essay attempts to nuance statements regarding Hearne's complicity in “emptying” the North by showing how the Journey establishes images of the Canadian North as neither completely barren nor fertile enough for settlement. Applying a natural-cultural contact zone perspective on Hearne's old text, I argue that the anthropocentric bias of the Journey's reception has impeded the realization that Hearne's zoological descriptions and sometimes sophisticated ecological contemplations owe much to the Denesuline who guide his travels. In part through his “beaver science”, Hearne deliberately opposes prospects of further colonization based on ideas of systemic expansion of the fur trade detached from the realities of local environmental conditions. His concern regarding the anthropomorphism and uncritical use of cultural metaphors in the emerging science of zoology nevertheless causes Hearne's “beaver science” to consolidate the distinctly anthropocentric and objectifying qualities of natural science that ultimately facilitate the exploitative activities of the Hudson's Bay Company.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.019 | 0.042 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| 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".