Generation and Transmission of Environmental Knowledge and Land Skills in Adaptation to Climate Change in Ulukhaktok, NWT
Bibliographic record
Abstract
This presentation reports on research that documents and describes how environmental knowledge and land skills are being generated and transmitted among Inuit in Ulukhaktok, Northwest Territories, Canada. In previous research in the Arctic, Inuit have expressed concern that as a result of rapid societal changes, the traditional modes of intergenerational knowledge transmission by which Inuit have developed the skills to hunt safely and successfully no longer function effectively. Younger generation Inuit are spending considerably less time involved in subsistence activities beyond organized land-camps and occasional hunting trips but comparatively more time engaged in formal education and wage employment. This has implications for culture, health and well-being, and for adaptation to changing climatic conditions. The transmission of 92 items of Inuit environmental knowledge and land skills was studied with a sample of 42 Inuit males between the ages 18 and 49 years in Ulukhaktok (approximately 50% of the potential sample). Data were collected through semi-structured interviews, free-listing and pile sorts. The general objectives of the interviews were to learn if an informant had learned a particular skill, if yes, who was their major teacher, how did they learn this skill, how old were they when they learned the skill, and what factors helped facilitate or impede transmission. The results are expected to inform initiatives to help facilitate the transmission of land skills and related environmental knowledge, many already underway, in the Inuvialuit Settlement Region and elsewhere in the Arctic.
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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 | 0.001 | 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 | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".