“Let Me Breathe of It”: A Circumpolar Literary and Ecological Perspective
Bibliographic record
Abstract
The commercial hunting of harp seal pups galvanized animal rights in the 1970s, culminating in the banning of sealskin products in Europe and the curtailment of trade in the United States. The seal in animal rights discourse is a type of object that needs saving in the form of protective measures to keep her safe from the rapacious greed of capitalism. However, in Indigenous discourse, the seal is another relative, a relation whose presence makes all certainties about hierarchy, use-value, moral exemption, and human exceptionalism impossible. This essay re-thinks the figural dimensions of seals in Yupiit and Inuit storytelling practices alongside debates around over-harvesting, competing global interests, and animal rights to develop current activism for environmental justice for both humans and seals in a time of rapid change. I suggest that focusing on practices of care rather than commodity circulation reframes the relationship of humans and seals beyond binary systems of interpretation that make humans subjects (with “culture”) and seals objects (in “nature”). Inuit stories, legal statutes, and environmental conservation rhetoric all appear to be different, if not contradictory, types of narratives. Nevertheless, when read together, they reveal a shared ethics of care for the wellbeing of the seal. This care, I suggest, momentarily frees seals from their entrapment in an economy of use and provides a basis for understanding the North as a lived environment.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.026 | 0.042 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".