Hunting with Polar Bears: Questioning Assumptions of Passive Property
Bibliographic record
Abstract
"Research in Canada's Arctic reveals that Inuit conceptualize both hunters and polar bears as active participants of the hunt and as part of a larger socio-economic system requiring the involvement of both humans and animals. The Inuit viewpoint creates serious conflicts with Western wildlife management systems that utilize a more traditional common property approach. This finding calls into question assumptions in common pool resource theories that treat natural resources as inherently passive and fully available for human appropriation. In fact, when polar bears are understood as active participants in the hunt, the rights of use, exclusion and transfer typically associated with property ownership in Western thought require significant revision. In this paper we present an argument for the incorporation of natural resources as worthy of consideration in common pool resource decisions and identify how a tenure system of active relationships operates in Arctic Canada. We offer this argument as one example of how a common pool resource may be managed within a larger socio-economic system without the attendant assumption that natural resources exist passively outside of ownership regimes."
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.044 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".