“We’re Made Criminals Just to Eat off the Land”: Colonial Wildlife Management and Repercussions on Inuit Well-Being
Bibliographic record
Abstract
Across Inuit Nunangat, Inuit rely on wildlife for food security, cultural continuity, intergenerational learning, and livelihoods. Caribou has been an essential species for Inuit for millennia, providing food, clothing, significant cultural practices, and knowledge-sharing. Current declines in many caribou populations—often coupled with hunting moratoriums—have significant impacts on Inuit food, culture, livelihoods, and well-being. Following an Inuit-led approach, this study characterized Inuit-caribou relationships; explored Inuit perspectives on how caribou have been managed; and identified opportunities for sustaining the Mealy Mountain Caribou. Qualitative data were collected in Rigolet, Nunatsiavut, Labrador, Canada through 21 in-depth interviews and two community open houses. Data were analyzed using constant comparative methods and thematic analysis. Rigolet Inuit described: how conservation management decisions had disrupted important connections among caribou and Inuit, particularly related to food, culture, and well-being; the socio-cultural and emotional impacts of the criminalization of an important cultural practice, as well as perceived inequities in wildlife conservation enforcement; and the frustration, anger, and hurt with not being heard or included in caribou management decisions. These results provide insights into experiences of historic and ongoing colonial wildlife management decisions, and highlight future directions for management initiatives for the health and well-being of Inuit and caribou.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.012 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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".