Fishing for Foresters: A New Institutional Analysis of Community Participation in an Aboriginal-owned Forest Company
Bibliographic record
Abstract
Aboriginal groups across Canada are looking for new ways to improve the living conditions of their people. Coast Tsimshian Resources LP is a forest company that is collectively owned by the Lax Kw'alaams band, a traditional fishing community in northern British Columbia. This research investigates the collectively-owned company as a possible creative means toward development, but in the process uncovers the significance of community 'embeddedness' in shaping development outcomes. Data was collected primarily through semi-structured and informal interviews with respondents from the community and company, among others. Interviews revealed the problem of a disconnection between the community and company. Through a New Institutional Analysis, which pays particular attention to context, the possible reasons for the disconnect are explored, and community 'embeddedness' is presented as a way of understanding it. Fishing is identified as a culturally salient practice and serves as a point of comparison to explain the lack of participation in the company's forestry activities. Suggestions for ways the company can work within this 'embeddedness' to ameliorate the disconnect are provided, and an elevated appreciation of the "sub-institutional elements" within New Institutional theory is suggested. Finally, the community-owned company is evaluated in terms of its ability to meet the development goals and visions of the Lax Kw'alaams band and First Nations in Canada.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.004 |
| 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".