Developing Human Well-being Domains, Metrics and Indicators in an Ecosystem-Based Management Context in Haida Gwaii, British Columbia, Canada
Bibliographic record
Abstract
Ecosystem-based management (EBM) encompasses both ecological integrity and human well-being, although it remains unclear how human well-being should be measured in an EBM context. Despite efforts to view EBM holistically, the human component is often overlooked or reduced to economic indicators that do not capture the full range of values held by the people affected by EBM policies. This study explored human well-being metrics of importance to local residents in Haida Gwaii, British Columbia (B.C.), Canada. The selection of this particular forest-dependent community was pragmatic since Haida Gwaii has recently participated in EBM planning and policy implementation that includes co-management between the Haida Nation and the Province of B.C. Using semistructured key informant interviews, we identified seven domains and 46 human well-being metrics important to measure on Haida Gwaii. Communities working to develop human well-being metrics in similar EBM contexts may find these concepts useful in their work.
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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 | 0.001 |
| 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) | 0.000 | 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".