Indigenous knowledge in sustainable forest management: Community-based approaches achieve greater success
Bibliographic record
Abstract
Forests continue to play a critical part in the spiritual and cultural life of Aboriginal people. In turn, Aboriginal people are striving to revitalize their role in maintaining a healthy relationship with these ecosystems. In Canada, the past two centuries have seen Aboriginal people largely excluded from forest management activities. This has begun to gradually change due to ongoing Aboriginal efforts in the courts as well as to national and international recognition of the potential contribution of Indigenous Knowledge to sustainable forest management. Such change is bringing about new opportunities for the meaningful involvement of Aboriginal people and Indigenous Knowledge in sustainable forest management activities. The increasing participation of Aboriginal people in sustainable forest management is both called for and reflected in various forest policies, practices and programs in Canada. While this represents a positive development, the degree and type of Aboriginal involvement called for have thus far generally been unsatisfactory from an Aboriginal perspective. Interviews conducted with both Aboriginal and non-Aboriginal participants in Ontario's new forest management planning process indicate that this recently developed process has nonetheless yielded some hopeful results in terms of Aboriginal involvement in certain instances. It was found that both Aboriginal and non-Aboriginal interview respondents most often described the Aboriginal consultation process to be a success where control over the nature and methods of sharing of information was relinquished to the participating Aboriginal communities. Contexts and implications of these findings are briefly discussed. Key words: Traditional ecological knowledge, native values mapping, Aboriginal forestry, sustainable communities
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.014 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".