Estimating Wildlife Harvest Based on Reported Consumption by Inuit in the Canadian Arctic
Bibliographic record
Abstract
The harvest and consumption of wildlife are integral to the livelihood, culture, and nutritional status of the Inuit of northern Canada. When wildlife populations are perceived to be vulnerable, harvest restrictions may be enacted to protect species conservation interests. Such restrictions may also have consequences for the nutrition and food security of Inuit communities. This study aims to estimate the harvest numbers of key wildlife species needed to sustain the traditional diet of Inuit. Using responses to the food frequency questionnaire that were collected from 806 men and 1275 women during the Inuit Health Study of 2007 – 08, we characterized annual country food consumption in five Inuit regions of northern Canada. Data on average edible yield of food species and Inuit population demographics were compiled and used to estimate the total number of harvested animals. Caribou (Rangifer tarandus) was the species consumed with the highest prevalence (> 90%) and in greatest amounts (29.6 – 122.8 kg/person/yr), depending on sex and region. The annual consumption rate for beluga whale (Delphinapterus leucas) was 5.9 – 24.3 kg per person, depending on sex and region, and that for ringed seal (Pusa hispida) was 4.1 – 25.0 kg per person. To sustain this consumption rate, it is estimated that a mean total of 36 526 caribou, 898 beluga whales, and 17 465 ringed seals are required annually. These results provide a baseline for food security and resource management in the Canadian Arctic to balance Indigenous subsistence needs and wildlife conservation.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".