Are community forestry principles at work in Ontario’s County, Municipal, and Conservation Authority forests?
Bibliographic record
Abstract
Ontario’s County, Municipal and Conservation Authority forests have received little attention within the academic literature on community forestry in Canada. These “Agreement Forests”, as they were once called, are a product of the early 20thcentury and have been under local government management since the 1990s. Most are situated in Southern Ontario. In this article we investigate the extent to which community forestry principles are at work in these forests. Three principles— participatory governance, local benefits and multiple forest use—are analyzed using a composite score approach derived from survey data collected from nearly all of these forest organizations (response rate = 80%). Results indicate that most of these organizations do display attributes associated with community forestry principles, including a local governance process, public participation activities, local employment and multiple-use management. Traditional forestry employment is less strong than in similar studies of Crown land community forests; however, there is an important emphasis on non-timber activities. The article concludes that the County, Municipal and Conservation Authority forests represents a unique approach, which reflects the specific geographic and socio-economic context in which it resides.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".