Social-ecological changes and implications for understanding the declining beluga whale (<i>Delphinapterus leucas</i>) harvest in Aklavik, Northwest Territories
Bibliographic record
Abstract
Subsistence is the basis for food access for Inuvialuit in the western Canadian Arctic and has strong economic, dietary, and cultural importance. Inuvialuit harvest beluga whale (Delphinapterus leucas (Pallas, 1776)) from the eastern Beaufort beluga population during summer months within parameters established through co-management. Over the past thirty years there has been a dramatic decline in the number of beluga harvested by Inuvialuit from the community of Aklavik, Northwest Territories. This paper investigates the potential drivers of change, both social and ecological, affecting the beluga harvest. Data were collected using 32 semi-directed interviews and experiential learning. Results revealed that ecological changes, notably coastal erosion at preferred whaling camps and unpredictable and severe weather have made harvesting more difficult, expensive, and often impractical. These changes are being experienced together with social changes including the loss of elders and their knowledge, and changing values and motivations for harvesting beluga. We conclude that no one driver is responsible for the decline in the beluga harvest, but rather it is the result of multiple social-ecological changes operating across scales that affect the feasibility of the harvest and motivation to participate. Isumatuyut ikayuqtuat avvakuyaa niqimun pimagaa Inuvialuit uataani Canadian Arcticmi nakuuyuq manik, niqilu, inuusiq nakuruallaktuaq. Inuvialuit katitait qilalugaq (Delphinapterus leucas (Pallas, 1776)) kivanmun Beaufort qilalugaq suli auyaqmi savaktiit. Sivulliqmi inuinnaq-qulit ukiuqmi mikliyuat tapqua qilalugaq katitait Inuvialuit Aklavik, Northwest Territoriesmi. Una makpiraaq ilisaqtuat anguniaqtuat, iluqatik inuuniarvikmi imaqmilu, tutqaanaittuq qilalugaq katitait. Kisitchiun katitait atugaa inuinnaq-qulit-malruknik apiqsiyuat asulu ilisaqtuat. Taimaagaa takupkagaa imaqmilu allauyuaq, taamna sallirq maqaigaa nuna taamna qilalugaqmun tanmaaq asulu allauyuaq silakluk asiin katitait tutqaanaittuq, akituyuqlu tutqaanaittuq. Taamna allauyuat illisaktuat atautchikun inuuniarvik ila tuquyuat innait asulu ilisimaruat, allauyuat pitqusiqlu ikayuqtuaq katitait qilalugaq. Uvagut taimagaa anguniaqti mikliyuat qilalugaq katitait taimagaa inugiaktut inuuniarvikmi imaqmilu allauyuaq savaktuat tutqaanaittuq asulu katitait ikayuqtuat ila taputiyaa.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".