Indigenous vision of a sustainable-use protected area: Ya'nienhonhndeh Protected Area case study
Bibliographic record
Abstract
In the Indigenous vision of a protected area in Canada, nature and culture are intrinsically linked. Conservation includes the preservation of traditional practices and land use, which requires versatility and flexibility. In 2010, the Wendat Nation initiated the Ya'nienhonhndeh protected area with Sustainable Use (PASU) project. This project combines the strict protection of an intact forest with exemplary resource use in areas altered by logging. This case study documents the vision of the Wendat Nation guiding this project. The protection of Wendat cultural and historical heritage lies at the heart of their vision. By preserving the intact forest, the Nation aims to pass down an unspoiled territory—a testament to the past and a forest as their ancestors once knew it. To ensure a win-win project for the region, the Nation adopts a pragmatic conservation approach, thereby preserving a heritage-rich territory while fostering partnerships with local stakeholders and ensuring the sustainable use of resources inside the protected area. Implementing the PASU will allow the exploration of exemplary forestry practices that align with preserving the Wendat's cultural and natural heritage. This study could inspire other Indigenous communities in their efforts to conserve their ancestral lands.
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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 | 0.011 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".