Indigenous Knowledge of bearded seal (<i>Erignathus barbatus</i>), ringed seal (<i>Pusa hispida</i>), and spotted seal (<i>Phoca largha</i>) behaviour and habitat use near Utqiaġvik, Alaska, USA
Bibliographic record
Abstract
Indigenous peoples possess information of animals’ habitat use and behaviour; information essential for management and conservation of species affected by climate change. Accessibility of species that are important to Indigenous hunters may also change with environmental conditions. We documented Indigenous Knowledge of bearded (ugruk in Iñupiaq), ringed (natchiq), and spotted seals (qasiġiaq) in Utqiaġvik, Alaska, USA, using semi-directed interviews with Iñupiaq hunters. This study originated from discussions with an agency of the regional municipal government to serve co-management efforts and understand habitat use of species subjected to climate change. Results indicated that ringed seals are associated with higher ice concentrations in winter than bearded seals and changes in sea ice retreat in spring may have greater impact on ringed seal habitat use because they are more likely to haul out on ice in spring. Additionally, all three species have foraging hotspots, used over several days by multiple individuals. Bearded seals, and to a lesser extent spotted and ringed seals, will use currents to forage. Results also revealed the use of inland water bodies and terrestrial habitat, which may become more important for bearded and ringed seals with changing ice concentrations and should be considered in management and conservation of these species.
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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 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".