Forest co-management in Northern Alberta: does it challenge the industrial model?
Bibliographic record
Abstract
The paper addresses the ability of forest co-management, within the Western Canadian provincial context, to co-exist with the industrial model of forestry. This paper draws on a two-year qualitative study of a new First Nation co-management process in Northern Alberta and a review of other First Nation forest co-management arrangements in Western Canada. Qualitative methods used included 23 semi-structured interviews with key co-management participants, non-participant observation of board and related meetings, and content analyses of previous board minutes. Our findings indicate that co-management has led to the incorporation of diverse values in forest management planning, cooperative relationships among parties to the Board, and shared decision making in forest management. We argue that co-management does not directly challenge the industrial model, but modifies it through a process of incremental change toward a more well-planned industrial presence in First Nation traditional territory. By giving a high priority to cultural sustainability criteria, First Nation participants in the co-management process in Northern Alberta challenge the forest industry to re-think the pace of development, the rates of return required to be profitable and measures to improve First Nation employment within the industry. Ultimately, tests of co-management success should incorporate First Nation priorities to maintain traditional and cultural practices in the context of industrial forestry. Such tests should evaluate the practice of provincial consultation requirements with First Nations, and cooperative efforts to develop Northern boreal forest resources. The success of co-management also depends upon industry practices to reduce the impacts of their activities on First Nation uses of the forest, and overall, on ecological evidence of sustainable forest management, including maintenance of biodiversity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".