Bibliographic record
Abstract
Comprehensive, census-type surveys of Inuvialuit harvesters were conducted in the Inuvialuit Settlement Region (ISR) in the 1960s (Area Economic Surveys) and 1970s (Inuit Land Use and Occupancy Project) and in the 1990s (Inuvialuit Harvest Study). These surveys, supplemented by other case studies, provide a basis for comparing Inuvialuit use of the Beaufort Sea and its resources in the 1960s and the 1990s. The geographic extent of harvesting was about the same in both decades. The number of harvesters grew, although by less than the rate of population growth. Mean annual harvest of country food per hunter declined from 2083 kg/yr to 707 kg/yr. The chief reason for the decline in harvest was the near-abandonment of dogs for transport. If we take into account the share of country food likely consumed by dogs, the per capita harvest of country food for human consumption may not have changed significantly between the two decades. What has changed, however, is the composition of the harvest: the ratio (by weight) of country foods from marine and terrestrial sources was 75:25 in the 1960s, but 45:55 in the 1990s. Available country food amounted to 115.2 kg/capita/yr in the 1990s, a significant contribution to the household economy. Thus, contrary to many predictions in the 1960s, subsistence harvesting persists as a significant economic as well as cultural preoccupation in the lives of Inuvialuit today. The results of this study suggest that the measurement of subsistence and commercial harvesting in terms of location, participation, inputs, and outputs is of continuing importance for fish and wildlife management and for economic planning.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".