Two Approaches to Ecosystem-Based Management in British Columbia, Canada
Bibliographic record
Abstract
My research examines two approaches to ecosystem-based management (EBM) in coastal British Columbia (B.C.) – Clayoquot Sound on the west coast of Vancouver Island and the Great Bear Rainforest (GBR) in the central and north coast of B.C. The first paper is an evaluation of the implementation of the Clayoquot Sound Scientific Panel’s (CSSP) recommendations, which introduced EBM in Clayoquot Sound. The second paper focuses on community-based monitoring by the Coastal Guardian Watchmen Network (CGWN) in the GBR and how they could incorporate lessons from other case studies around the world. The CGWN is a network of stewards from ten First Nations communities in the GBR, who monitor their natural and cultural resources. Together, these two papers provide insights into new approaches to conservation that are collaborative and holistic, incorporating local knowledge and concerns.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.015 | 0.005 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".