Agroforesterie en développement : parcours comparés du Québec et de la France
Bibliographic record
Abstract
This analysis draws a parallel between France and Quebec agroforestry in terms of five fundamental issues: recognition, interdisciplinarity and collective approach; knowledge acquisition and transfer; status, regulations and funding; awareness and engagement; and technical support and field implementation. For Quebec, the basic information is taken from an agroforestry forum held by the Centre de référence en agriculture et agroalimentaire du Québec in March 2010. Wind-breaks and tree riparian buffers are becoming increasingly common, mainly for environmental reasons, while silvoarable systems remain less common. In France political recognition has been achieved and a number of regulatory restrictions have been lifted; however, in Quebec the status of trees outside forests remains unclear, regulations are restrictive and programs are ill suited. Agroforestry systems perform many ecosystem services, but work remains to be done to quantify them and determine their potential in terms of agricultural and timber production.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".