Reviewing Canada's National Framework of Criteria and Indicators for Sustainable Forest Management
Bibliographic record
Abstract
The Canadian Council of Forest Ministers' (CCFM) framework of Criteria and Indicators (C&I) for Sustainable Forest Management, published in 1995, provide a science-based framework to define and measure Canada's progress in the sustainable management of its forest. In 2001, the CCFM launched a review of its C&I to ensure the continued relevance of the indicators to Canadian values and to improve the ability to report on indicators. This paper describes the threestep review process, which engaged a broad array of representatives of various sectors of society. First, focus groups were used to identify public values, issues and concerns with respect to the sustainable use of Canada's forest. Second, technical experts from across the forest sector revised the indicators. Third, the revised C&I were validated with users of the framework. The revised framework, released in September 2003, consists of six criteria and 46 indicators. The number of indicators has been reduced, compared to the 1995 framework, by focusing on indicators that are most relevant to Canadians' values, are most often measurable with available data, and are understandable to policy makers, forest managers and an informed public. Links between criteria are better defined and, in some cases, indicators address multiple values under different criteria. A number of tools and techniques originally developed for use at the sub-national level were adapted for use at the national level in this review. Canada's experience with reviewing its indicators may serve as an example and model to other countries now considering reviewing their national C&I frameworks. Key words: Canada, Canadian Council of Forest Ministers, criteria and indicators, C&I, sustainable forest management, review
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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 | 0.143 | 0.215 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.049 | 0.064 |
| Science and technology studies | 0.014 | 0.010 |
| Scholarly communication | 0.017 | 0.005 |
| Open science | 0.011 | 0.005 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".