Bibliographic record
Abstract
he Canadian Model Forest Network (CMFN) has matured and grown over the past two years, successfully navigating its transition to a non-profit organization.It marked its first full year of operation as an independent organization and officially welcomed the Canadian Forest Service (Forest Communities Program) as a partner with a special event during for its semi-annual meeting in Ottawa Jan. 13-15, 2009.Long known for their leadership role in advancing sustainable forest management, Canada's Model Forests are now extending their focus beyond the resource to helping advance the sustainability of communities that depend on the forest.Natural Resources Canada, through the new Forest Communities Program, is supporting individual Model Forests and the Network in these endeavors.As a result of this expansion in scope, the CMFN has grown to 14 members, adding Lac-Saint Jean Model Forest and Le Bourdon Project in Quebec, Northeast Superior Forest Community in Ontario, and Clayoquot Forest Community in British Columbia.These four join existing members: Newfoundland and Labrador Model Forest, Nova Forest Alliance, Fundy Model Forest, Eastern Ontario Model Forest, Manitoba Model Forest, Prince Albert Model Forest, and Resources North Association, which has evolved from the McGregor Model Forest.Foothills Research Institute (formerly Foothills Model Forest), Lake Abitibi Model Forest and Waswanipi Cree Model Forest complete the current Network.Guiding the Network during this new phase is General Manager Dave Winston R.P.F., who joined the Network in February, 2008 following a career spanning over 42 years in forestry, including three years as a forestry consultant and 37 years as a research director and scientist with the Canadian Forest Service in Ottawa, Victoria, Petawawa and Sault Ste Marie."One of the Network's unique strengths is our ability to bring resources and groundlevel perspectives from across regions and our membership to bear on specific areas of common concern.For example, the CMFN has been working with the Canadian Federation of Woodlot Owners to examine the concept of payment for ecological goods and services, which is emerging as a public policy issue, " Winston said."At the Network level, we are also active in addressing several other strategic initiatives including nontimber forest products, bioenergy, the boreal forest, carbon accounting, youth training and socio-economic indicators of community development." In addition, Canada's Model Forests are playing a major international role in partnership with Canada's International Development Research Centre (IDRC) and the International Model Forest Network Secretariat (hosted by CFS) in providing research funding and advice to Model Forests throughout the world and also developing a strategy to expand this role in the future.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.152 | 0.028 |
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".