“Connected to the land and to each other”: clam harvesting, Inuit community health, and wellbeing in Nunavut
Bibliographic record
Abstract
Inuit communities in Nunavut hold deep and intricate relationships with country food that are integral to daily life, health, and wellbeing. Clams ( Mya truncata) (ᐊᒻᒨᒪᔪᐃᑦ) provide important sustenance for many Inuit communities, yet research focused on the role of clams in supporting community health is rare. We sought to characterize clam use in the Qikiqtani region of Nunavut, Canada using a community-led approach, in-depth conversational-style interviews, and reflexive thematic analysis. Inuit knowledge holders expressed the importance of clams for physical and nutritional health, mental and social wellbeing, and community connection and culture. Clams were described as an accessible source of nutrition supporting food sovereignty, while clam harvesting promoted sharing of Inuit knowledge and skills, and a community-centered approach to food systems. Inuit knowledge holders also discussed changing country food systems and the impacts of these changes on diet, sharing practices, and the environment. This research illustrates the holistic relationship that exists between country food systems, community health and wellbeing, and the environment, highlighting not only the importance of clams for Inuit communities but also the critical role of Inuit voices, lived experiences, and perspectives in ecosystem health.
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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 | 0.002 | 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 | 0.013 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 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".