Canada's privately owned forest lands: Their management and economic importance
Bibliographic record
Abstract
Canada has the third largest area of forest in the world after Russia and Brazil. About 89% is in public ownership; 11%, or 23 million ha, is privately owned. The comparatively small area of forest in private ownership has been largely overlooked. If it were a national forest, it would be the 11th largest in the world, between Japan and Finland, with the 8th largest production of industrial roundwood, between Finland and Germany. Canada's privately owned forest lands produce 19% of our wood supply, some 36 million m3 per year. There are about 425 000 owners with an average of 45 ha each. Their objectives vary greatly. They own a high percentage of the Deciduous, Great Lakes-St. Lawrence and Acadian Forest Regions. These forests are very important environmental, economic and social resources. We should understand their value better and set in place management programs to ensure their health and productivity. Landowner's rights and management objectives must be respected. Key words: private forest land, Canada, wood production, area of forest, management programs
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".