The Harvest of Beluga Whales in Canada's Western Arctic: Hunter-based Monitoring of the Size and Composition of the Catch
Bibliographic record
Abstract
Hunter-based beluga monitoring programs, in place in the Mackenzie Delta since 1973 and in the Paulatuk, Northwest Territories, area since 1989, have resulted in collection of data on the number of whales harvested and on the efficiency of the hunts. Since 1980, data on the standard length, fluke width, sex, and age of the landed whales have also been collected. The number of belugas landed each year averaged 131.8 (SD 26.5, n = 1337) between 1970 and 1979, 124.0 (SD 23.3, n = 1240) between 1980 and 1989, and 111.0 (SD 19.0, n = 1110) between 1990 and 1999. The human population increased during this same period. Removal of belugas from the Beaufort Sea stock, including landed whales taken in the Alaskan harvests, is estimated at 189 per year. The sex ratio of landed belugas from the Mackenzie Estuary was 2.3 males:1 female. Median ages were 23.5 yr (47 growth layer groups [GLG]) for females (n = 80) and 24 yr (48 GLG) for males (n = 286). More than 92% of an aged sample (n = 368) from the harvest consisted of whales 10 or more years old (20 GLG). The rate of removal is small in relation to the expected maximum net productivity rate of this stock. The continued availability of large, old individuals after centuries of harvesting and the apparent lack of change in the size and age structure of the catch in recent years also support a conclusion that the present level of harvest is sustainable.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".