Inuvialuit Youth and Adaptation to Climate Change
Bibliographic record
Abstract
Arctic communities have undergone rapid changes in the past half century. In recent years, communities have been exposed to additional stresses associated with climate change. These changes have transformed harvesting practices, community social networks, cultural and spiritual traditions, and have been linked to loss of identity and its associated social problems. In research conducted with the community of Ulukhaktok, Northwest Territories, Canada, community members identified specific concerns over the vulnerability of community youth. Adult community members and educators point to the potential loss of traditional land-based skills coupled with lack of workplace-relevant skills among the growing population of young Inuvialuit. For example, the role played by technology, globalization, and loss of language in conditioning how Inuvialuit youth experience and respond to climate change remains largely unexplored. In response to this community-identified research need, research is being undertaken in Ulukhaktok together with youth, elders and educators to identify how social change and climate change interact to affect the well-being of community youth, and to identify means for strengthening adaptive capacity. In previous research, youth expressed concerns including: lack of competency standards in education; limited employment; inadequate housing; drug and alcohol abuse; loss of language; and loss of traditional land-based skills. This research builds on these concerns and involves community youth in applied-participatory research through a host of methodological tools including: focus groups, participatory mapping, analysis of secondary sources, and the use of the Internet and video technologies. This paper describes the context for this new research and reports on preliminary findings.
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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 | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".