Evolving ecosystem management in the context of British Columbia resource planning
Bibliographic record
Abstract
Ecosystem management is an approach to natural resource planning that theoretically places environmental issues on an equal footing with the economic concerns that dominate resource use. This approach recognizes the importance of both a healthy environment and access to natural resources. Each of these factors is an implicit element of human security, a political concept that promotes the protection of human lives and livelihoods. Ecosystem management acknowledges the role of humans as an integral part of the ecosystem; however, it does not define the ways in which humans and the ecosystem interact. This lack of definition makes the practical application of ecosystem management difficult.In this paper, we examine the application of ecosystem management principles in British Columbia's Clayoquot Sound. We propose that human security can act as an imperative for the expanded consideration of social networks and environmental pathways in the practice of ecosystem management. Theories from the social and natural sciences are supplied to support the science-based application of ecosystem management. These underpinnings enable managers to better define ecosystem boundaries and to integrate expanded social networks into management plans.
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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 | 0.001 | 0.003 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".