Sustainable tourism development and Indigenous protected and conserved areas in sub-arctic Canada
Bibliographic record
Abstract
Rural and northern Indigenous communities across Canada are pursuing new Indigenous-led conservation partnerships with Crown governments as critical alternatives to Western conservation and extractive industries regimes. Colonial conservation policies and industrial development continue to displace Indigenous Peoples from their ancestral territories, with great consequences to land-based economies, food security, and knowledges. Indigenous-led conservation is an umbrella term used to describe a variety of initiatives that includes Indigenous Protected and Conserved Areas. Indigenous communities lead the creation, management, and stewardship of these protected areas, which are guided by localized knowledge and priorities. This creates unique opportunities to build new and bolster existing tourism businesses with sustainable socio-economic, cultural, and environmental outcomes. Our research examines Indigenous-led conservation and tourism in the Dene/Métis community of Fort Providence, Northwest Territories, located adjacent to Canada's first official Indigenous Protected and Conserved Area, Edéhzhíe. Guided by Indigenous methodologies and collaborative approaches, this paper presents the analysis of 23 semi-structured interviews with Elders, knowledgeable land users, and community members. While tourism development in the community is currently limited, our results indicate that participants are hopeful about the contributions of Edéhzhíe and tourism to sustainable economies, cultural resurgence, and environmental stewardship in the surrounding communities. Participants demonstrate that Indigenous-led conservation and tourism have the potential to challenge existing colonial, capitalist land use regimes and foster Indigenous governance, reconciliatory processes, and environmental resiliency. Our findings can be used by other Indigenous communities to inform conservation and sustainable development goals related to regional tourism economies.
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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 | 0.003 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".