Aboriginal forest tenure and governance in British Columbia : exploring alternatives from a Stellat'en First Nation community perspective
Bibliographic record
Abstract
The purpose of this research is to contribute to the identification of appropriate forest tenure and governance designs that are in congruence with Aboriginal values, interests and rights. The research is highly relevant to current societal deliberations on sustainable forest management as well as to the future of the forest sector in Canada. First Nations culture and ways of life are intimately and inextricably tied to the land. Some eighty percent of Canada’s First Nations communities are situated in productive forest regions (NAFA 2003). Even so, First Nations have been largely excluded from forest development and planning activities. Furthermore, the provincial policy emphasis on industrial timber production may not be consistent with Aboriginal forest values. This community-based research takes a participatory approach to forest policy analysis. The work is conducted in partnership with the Stellat’en First Nation and Carrier Sekani Tribal Council in central British Columbia. Stellat’en criteria for forest tenure and governance are identified in a series of workshops and interviews. These criteria are then applied in the analysis of four alternative models: the Community Ecosystem Trust, the Gitanyow joint land use planning model, BC Community Forest Agreements and Aboriginal reservations in the United States. The results indicated that Stellat’en have three main goals regarding forest tenure and governance: protect the traditional territory for future generations, protect Stellat’en culture and support Stellat’en economic self-determination. Implementation of the Stellat’en vision calls for a greater emphasis on ecological and cultural values in forest management, devolution of decision making authority to First Nations, reallocation of harvesting rights and redistribution of wealth generated by forest activities. The Stellat’en perspective emphasizes co-existence and stewardship. Evaluation of the four alternative models provided useful insights for progressive tenure and governance design. All four models had positive aspects to contribute, as well as shortcomings. The models are not mutually exclusive. Since each model addresses different management and institutional functions, they could be combined into a new system for the future.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.020 | 0.007 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".