Temperate Agroforestry Development: The Case of Québec and of France
Bibliographic record
Abstract
This study sought to shed light on the political and organizational dynamics favoring the deployment of agroforestry in temperate environments. Development paths of agroforestry practices in Québec (Canada) and France were analyzed regarding five different issues: political status and recognition, regulation and financing, knowledge acquisition, knowledge transfer and training, development actors and implementation in the field. Scientific studies and results continue to accumulate concerning temperate agroforestry and its environmental benefits. Political recognition of the field appears to be stronger in France (and the EU), which makes state financial aid conditional upon the adoption of the practices. In Québec, only the Ministry of Agriculture provides limited support. It financially assists research at a moderate level, as well as the installation and maintenance of trees by participating farmers to perform specific functions, i.e., erosion control, water quality, and biodiversity. A large number of actors are active in France, where efforts are being made to improve consultation and to reduce redundancy. Stakeholders in Québec are linked to the broader agri-environment field and act partially through agroforestry, according to varying degrees of competency, creating a disparity between regions. Recognition at the highest level, i.e., training for councillors and advisors, greater flexibility in obtaining assistance, inclusion of a greater diversity of systems, and a structure that ensures promotion and consultation, would favour the further development of agroforestry in the industrialized nations of the temperate zone.
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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 | 0.000 | 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".