2Environmental and Health Benefits of Hunting Lifestyles and Diets for the Innu of Labrador Summary
Bibliographic record
Abstract
The Innu of Northern Labrador, Canada have undergone profound transitions in recent decades with important implications for conservation and health policy. The change from permanent nomadic hunting, gathering and trapping in `the country ’ (nutshimit) to sedentary village life (known as ‘sedentarisation’) has been associated with a marked decline in physical and mental health. The overarching response of the national government has been to emphasize village-based and institutional solutions. We show that changing the balance back to country-based activities would address both the primary causes of the crisis and improve the health and well-being of the Innu. Drawing on ethnographic fieldwork, interviews with Innu older people (Tshenut), empirical data on nutrition and activity, and comparative data from the experiences of other indigenous peoples, we identify pertinent biological and environmental transitions of significance to the current plight of the Innu. We show that nutrition and physical activity transitions have had major negative impacts on individual and community health. However, hunting and its associated social and cultural forms is still a viable option as part of a mixed livelihood and economy in the environmentally-significant boreal forests and tundra of Northern Labrador. Cultural continuity through Innu hunting activities is a means to decelerate, and possibly reverse, their decline. We suggest four new policy areas to help restore country-based activities: i) a food policy for country food; ii) an outpost programme; iii) ecotourism; and iv) an amended school calendar. Finally, we indicate the implications of our analysis for people in other countries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".