Saviors, “sealfies,” and seals: strategies for self-representation in contemporary Inuit films
Bibliographic record
Abstract
The legibility of the inter-relationships between human and seal is what is at stake when Inuit present themselves within administrative discourses at international assemblies in defense of their ontology and the right to hunt seals. In the language of administration and in the narrative practices of international animal rights, seals can only appear in a predetermined categorical framework for what constitutes human ethical responsibility to nature. The seal in animal rights discourse is one 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 cultural practices, the seal is another relative, a relation whose presence makes all certainties about hierarchies, use-value, moral exemptions, and human exceptionalism impossible. Using the trending social media phenomenon of the “sealfie” and three contemporary northern Indigenous films, this essay argues that the Inuit use of these media formats showcases their cultural and economic dependence on seal hunting and restructures debates around authority, self-representation , and one-sided environmental protection activities.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.017 | 0.022 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".