Inuvialuit traditional ecological knowledge of beluga whale (Delphinapterus leucas) under changing climatic conditions in Tuktoyaktuk, NT
Bibliographic record
Abstract
This paper documents Inuvialuit traditional ecological knowledge of beluga, including ecology and behavior, hunting techniques, and food preparation under changing climatic conditions in Tuktoyaktuk, NT. Beluga whale (Delphinapterus leucas) is an important food source for Inuvialuit in the western Canadian Arctic, a region that is experiencing dramatic climate change. Data were collected using semi-directed interviews with 17 Inuvialuit beluga harvesters and participant observation. The research found that Inuvialuit beluga harvesters possess detailed rational knowledge of beluga, particularly regarding hunting techniques and food preparation, both which are guided by a moral code about how to behave with respect to beluga. In terms of beluga ecology and behavior, Inuvialuit knowledge is limited to anecdotal reasoning drawing on generalized observations of beluga and the accounts of others. Inuvialuit are experiencing the effects of climate change, but seem to be coping thus far in the context of beluga harvesting but ongoing change in the region may increase the risks associated with hunting and preparing beluga in the future.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| 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".