Inuit uses of weather, water, ice, and climate indicators to assess travel safety in Arctic Canada, Alaska, and Greenland: a scoping review
Bibliographic record
Abstract
Environmental indicators are naturally occurring variables, conditions, and events that are used to assess and monitor environmental conditions and change. Inuit throughout Inuit Nunaat (Inuit circumpolar homelands) observe and experience environmental indicators as they travel year-round for harvesting and other cultural practices. Inuit draw on their observations of current conditions and their knowledge of weather, water, ice, and climate (WWIC) indicators, when seeking to predict and understand conditions that impact safe travel. This scoping review documents the types and diversity of WWIC indicators articulated in peer-reviewed and grey literature as being used by Inuit in Canada, Alaska, and Greenland to assess travel safety. Two reviewers independently screened 512 studies using pre-determined eligibility criteria and 123 studies were included for review. A total of 163 unique WWIC indicators were used across 85 communities in Canada, Alaska, and Greenland. Indicators reflect a broad range of ways that Inuit experience their environment, through sight, feel, and sound. Indicators can be considered as causal, conditional, or predictive (or a combination thereof), where knowledge of the interactions among various indicators is especially important to support safe travel. Identified gaps and future research directions included assessing key indicators to better target development of locally relevant research and information services.
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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 | 0.010 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.017 | 0.022 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".