Comparing the social values of forest-dependent, provincial and national publics for socially sustainable forest management
Bibliographic record
Abstract
A mail survey was conducted of local residents of a forest-dependent region (Fraser Fort George Regional District, n=974), provincial (British Columbia, n=1208) and Canadian (n=1672) publics to compare their values for forests and preferences for forest management (overall response rate=45.2%). While the local public tended to place a significantly higher (p<0.05) emphasis on economic values and clearcutting practices relative to provincial and national publics, all publics held quite similar views on forest management overall. All publics support a multi-value/ecosystem management over a single-value/timber management approach to forest management, do not support maximisation of economic returns from timber regardless of the impacts and agree forest managers should be more responsive to local resident values than the values of more distant groups. Responses also reflected a lack of public confidence in government natural resource agencies. Results suggest residents from forest and non forest-dependent communities share similar forest values, that current forest management practices such as clearcutting do not reflect the values of local, provincial or national publics, and that forest managers should be especially responsive to the values of the local public when making forest management decisions. Key words: social values, forest policy, public participation, socially sustainable forest management
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".