'Fresh seal blood looks like beauty and life': #Sealfies and subsistence in Nunavut
Bibliographic record
Abstract
In this paper, I analyze the various functions, meanings and affects associated with seal hunting, eating and sharing seal meat, wearing sealskin clothing and posting #sealfies. Drawing on several decades of research with hunting and gathering families in the eastern Canadian Arctic, and starting with the cultural premise that hunting seals unites the worlds of humans, animals, and spirits, I argue that the seal is a prominent metaphor for the Inuit self. By extension, I examine how Inuit use #sealfies as an extension of other subsistence practices, as a way of making identity (personal and collective), and as a way of countering the negative stereotypes used by animal rights activists to condemn hunting in general. #Sealfies have become an important resource in the subsistence toolkit of contemporary Nunavut Inuit foragers, providing an effective platform for defending their foraging traditions and for creating a meaningful and modern 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".