“Everything We Do, It's Cedar”: First Nation and Ecologically-Based Forester Land Management Philosophies in Coastal British Columbia
Bibliographic record
Abstract
People's values and attitudes regarding the natural world determine the level of care with which they approach the use of natural resources. We studied how human relationships with nature influence people's actions, using western redcedar (Thuja plicata), a major forest tree of northwestern North America, as a study system. Semi-structured interviews were conducted with eleven Northwest Coast Indigenous plant experts and eleven ecologists and foresters of mixed European descent with an ecologically-oriented perspective in coastal British Columbia. The transcripts were analyzed using NVivo qualitative data analysis software for emerging themes. Results demonstrate more commonalities than differences between the two groups; they both expressed a personal—often spiritual—connection with nature and both value long-term and interdisciplinary management strategies. First Nation individuals have a unique spiritual relationship with western redcedar that is linked to both everyday and ceremonial practices, while ecologically-based foresters and ecologists have personal and academic relationships broadly with nature. They have similar environmental concerns of damage from industrial forestry practices, particularly the loss of old growth forests, and the negative effects of climate change. Our results support the assertion that First Nation perspectives are equally scholarly as the foresters’ perspectives are reverential, and people from varied cultural backgrounds can care for the environment in similar ways. Moreover, an interdisciplinary approach that unifies science with Indigenous teachings can encourage a new moral framework for forestry management that values resources beyond commodification.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.024 | 0.014 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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 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".