Evaluating the transition to sustainable forest management in Ontario’s Crown Forest Sustainability Act and forest management planning manuals from 1994 to 2009
Bibliographic record
Abstract
The purpose of the paper is to analyse the extent of policy change and learning in the 20 years following the implementation of Ontario’s forest sustainability legislation. Extent of policy learning and change towards sustainable forest management are measured using a combination of content, co-occurrence, and textual analysis of the previous Crown Timber Act and the new Crown Forest Sustainability Act, as well as the latter’s 1996 and 2009 forest planning manuals. There were four key findings. First, policy change towards sustainable forest management has been limited. Second, although there was an increased number of values mentioned in new legislation and planning manuals, the frequency of timber values remained dominant. Third, although integration occurred among a greater range of values, integration with timber values continued to dominate. Fourth, with respect to policy learning, the achievement of sustainable forest management is now explicit and judged based on evidence regarding the inclusion of a range of values beyond timber. The paper concludes that the transition to the more integrative and responsive policies of sustainable forest management remains a work in progress.
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".