Canada's Model Forests 20 years on: <scp>t</scp>owards forest and community sustainability?
Why this work is in the frame
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Bibliographic record
Abstract
We review how Canadian Model Forests pursued forest and community sustainability over the course of two decades (1992–2012). Given its roots in the forest industry and forest science, Model Forest programming initially faced some challenges in pursuing the socio‐economic dimensions of sustainable forest management ( SFM ) in order to fulfil mandated community sustainability objectives. This was due, in part, to how objectives, stakeholders, and expertise were brought together to develop SFM . The programme helped to define sustainability and the SFM paradigm, advance forest science and social research, and bring together a mix of usually adversarial partners in the name of innovation. Ultimately, the termination of federal programming was linked to high‐level policy shifts, yet difficulty in delivering on the socio‐economic dimensions of SFM during a period of forest sector and community crisis was also a factor.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it