Canadian Council of Forest Ministers: Champions of sustainable forest management
Bibliographic record
Abstract
The Canadian Council of Forest Ministers (CCFM), established in 1985, is composed of the federal, provincial and territorial Ministers responsible for forests. Its role has evolved into one that stimulates the development of policies and initiatives for strengthening the forest sector, including the forest resource and its use. One of the most important functions of the CCFM is that it sets the overall direction for the stewardship and sustainable management of Canada's forests by addressing issues and stimulating joint initiatives. Under its guidance, four successive National Forest Strategies and three Forest Accords have been developed. Another major achievement has been the development of the CCFM Criteria and Indicators Framework: Defining Sustainable Forest Management A Canadian Approach to Criteria and Indicators. Today, the CCFM works under five strategic themes: sustainable forestry; international issues; forest communities; science and technology; and information and knowledge. The ongoing, positive cooperation between the two levels of government helps maintain healthy and productive forests and their sustained contribution to Canadians' economic, environmental and social well-being over the long term. Key words: stewardship, governments, collaboration, national framework for action, criteria and indicators, integrated information
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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 | 0.012 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".