Indigenous Fish and Wildlife Co-management as an Opportunity to Support Inuit Well-being
Bibliographic record
Abstract
Inuit in the Circumpolar North are closely tied to the lands, waters, and wildlife, which underpin livelihoods, food, cultural continuity, and well-being. Co-management institutions in Canada—arising from Inuit treaties—were created to increase the inclusion of Inuit voices and Inuit knowledge in recommendations about wildlife management. Co-management decisions have important implications for Inuit well-being; however, research has yet to explicitly explore how co-management decisions can enhance and impact Inuit well-being. Therefore, this dissertation research characterized how wildlife co-management impacts well-being in Inuit Nunangat. An Indigenous co-management-led research approach was used, which drew from decolonizing methodologies, boundary work theory, and community-based research principles. First, systematic critical review methods uncovered no publications that explicitly analysed co-management from a health or well-being lens; however, social determinants of health were implicit and prevalent in the literature. Responding to this research gap, data were then collected through conversational research interviews with co-management practitioners throughout Inuit Nunangat (n=21 interviews), and with Inuit in Nunatsiavut (n=21 interviews). Qualitative data were deductively and inductively analysed using a constant comparative method and thematic analysis. Co-management practitioners described how co-management institutions can act as boundary work organizations and how the social determinants of health could be integrated inside the shared space of co-management. Nunatsiavut Inuit underscored the importance of considering the determinants of health in co-management decision-making processes. For instance, Inuit explained how historic 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 they experienced with not being heard or included in caribou management decisions. Similarly, Inuit reflected on how commercial fisheries remain a social struggle with multiple injustices, and identified opportunities for Inuit well-being indicators to be integrated into baseline monitoring and to measure progress. These results provide insights into experiences of historic and ongoing colonial wildlife management decisions, and highlight future directions for co-management initiatives—emphasising the health and well-being of Inuit and wildlife.
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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 | 0.003 | 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 | 0.010 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.009 |
| 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".