Fish and Marine Mammals Harvested near Ulukhaktok, Northwest Territories, with a focus on Anadromous Arctic Char
Bibliographic record
Abstract
Fish and marine mammals are an important traditional subsistence and cultural resource for residents of Ulukhaktok, a community within the Inuvialuit Settlement Region, Northwest Territories. Community-based harvest surveys were conducted monthly out of Ulukhaktok, between 2004 and 2015, to enumerate fish and marine mammal subsistence harvest. Anadromous Arctic Char (annual average: 3,464 fish), Lake Trout (annual average: 2,114 fish), and Ringed Seals (annual average: 256 seals) continue to be the most abundantly harvested fish and marine mammal species 2004–2015, with landlocked Arctic Char (annual average: 203 fish), whitefish (annual average: 74 fish), cod (annual average: 136 fish), and Bearded Seals (annual average: 8) also reported. Accessibility to harvesting areas and availability of fish and marine mammals were strongly linked to seasonal cycles. Following concerns regarding the population status of Kuujjua River (i.e., Tatik Lake) Arctic Char, and to support the sustainable management of all Arctic Char subsistence and commercial fisheries in the area, the Ulukhaktok Char Working Group (UCWG) was established in 1996. The UCWG implemented a community fishing plan with voluntary management measures and fishery guidelines supported by harvest data provided by monitoring programs. In response to the observed decline in stock status, the UCWG established a voluntary subsistence harvest level of 1,000 fish from Tatik Lake which has not been surpassed in recent years (2003–2015); however, the total number of Kuujjua River Arctic Char harvested is unknown due to the uncertainty regarding contributions to the coastal mixed-stock harvest. Total annual harvest of anadromous Arctic Char from respective management zones 1988–2015 varied as follows: a) between 486 and 6,297 fish in coastal waters; b) between 0 (voluntary community closure) and 4,386 fish from the Kuujjua River; and c) between 0 and 5,502 fish from rivers in Prince Albert Sound. Co-management partners consider all available information collected through harvest surveys, monitoring programs, Indigenous Knowledge and observations, and scientific research to support the adaptive co management of these important fish and marine mammal species in a changing climate.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 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".