Inuit Perception of Marine Organisms: From Folk Classification to Food Harvest
Bibliographic record
Abstract
To survive in the Arctic, the Inuit have developed a unique relationship with the marine environment and its living organisms. Unlike large marine mammals, the importance of smaller marine organisms for food, health, and wellbeing is largely undocumented. To call attention to these components of the food system in Nunavik, in northern Québec, and to understand their importance for health and wellbeing, Elders in two Inuit communities, Ivujivik and Kangiqsujuaq, were interviewed in May 2014. The objectives of this study were to: 1) document all marine organisms harvested and consumed in these communities; and 2) highlight the importance of these country foods through their position within the Inuit zoological classification, as well as their perceived contribution to health and wellbeing. Fifty-seven species of marine organisms were identified as part of the past or current food system, including birds, mammals, fish, mollusks, crustaceans, echinoderms, and algae. Harvesting location is an important characteristic in the local classification. Nearly a third of all organisms listed can be harvested on the seashore and are collectively called tininnimiutait, which derives from seashore (tininniq) and includes seaweed, shellfish, and certain fish. Tininnimiutait differ from irqamiutait, which come from the bottom of the water (irqa). Furthermore, irqamiutait are a relatively recent addition to the diet that have the potential to positively impact health. Activities related to the harvest and consumption of these organisms are often associated with health and wellbeing. The abundance of tininnimiutait, their proximity to the land, and year-round accessibility make them an important food source today, particularly in light of growing concerns related to climate change, lifestyle and dietary transitions, food security, and sovereignty in the North.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".