Tuktu and environmental change: Inuit caribou harvesting on southern Baffin Island
Bibliographic record
Abstract
Up to this point there has been relatively little research that has examined human-caribou interactions in the context of multiple natural and human stresses. Previously the focus of management studies has been on the co-management structures and their function. By addressing community interactions with caribou on Southern Baffin Island in the context of changing access, climate-driven caribou population changes, and evolving management frameworks and institutions, this study aims to develop a baseline understanding of the sustainability of caribou harvesting in the Iqaluit region. Drawing attention to caribou as a major source of country food, and a species that is sensitive to climate change impacts, the study will be a resource for land-use planners and policy-makers on the importance of preserving biodiversity and sustainable northern ecosystems from ecological, cultural and food security perspectives. The work helps to refocus attention on sustainable harvesting and co-management as a key adaptation and resiliency strategy in the face of a rapidly changing Arctic. Working closely with community members, and building upon over 6-years of previous research in Iqaluit, the thesis examines how hunters are adapting their behaviors to changing access to harvest areas and variations in caribou populations. This is considered against the backdrop of adaptive changes within the territorial institutions and organizations that are engaged in wildlife management.
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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 | 0.000 | 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 | 0.007 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".