Forest Management in New Brunswick: the Jaakko Pöyry Study, the Legislative Select Committee on Wood Supply, and where do we go from here?
Bibliographic record
Abstract
In late 2001, the New Brunswick Forest Products Association submitted a letter to the New Brunswick Minister of Natural Resources, which triggered a three-year sequence of events whose potential to change New Brunswick forestry is more profound than any development since passage of the Crown Lands and Forests Act 25 years ago. Forestry in New Brunswick has risen to a level of prominence in the public and professional consciousness that is unprecedented in recent decades; the public voice is louder and stronger, industrial concerns are greater, and the economic vulnerability of the province is clearly evident. In this paper, we chronicle these events and identify some resulting and important challenges that confront the New Brunswick forestry community as it faces the future. The forestry community faces huge challenges to create a healthier forest and forest economy, which will require concerted, coordinated, and constructive efforts of practitioners, researchers, and policy-makers from the domains of social, management, and environmental science. Key words: forest policy, intensive forest management, public hearings, public participation, future directions of Crown land management
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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 | 0.004 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".