The Quebec Model of Agricultural Extension: A Publicly Led and Regionally Driven Approach through the Programme services-conseils
Bibliographic record
Abstract
As agricultural extension systems adapt to challenges like climate change, labour shortages, and the demand for sustainability, the Quebec model offers a distinctive approach grounded in public leadership and regional delivery. At its core is the Programme services-conseils (PSC), which provides financial support for farmers to access accredited, independent advisory services. Coordinated provincially and delivered through regional networks (Réseaux Agriconseils) with support from the Coordination services-conseils, the program ensures services remain accessible, high-quality, and responsive to local realities. Producers receive a subsidy that reimburses a portion of their advisory service costs, with funding coming from government sources. Advisors funded through the PSC are neutral and independent, with no ties to input suppliers—an approach that contrasts with models where advisory services are linked to product sales. While publicly supported, services are not free; producers contribute to reinforce value and accountability. The PSC offers supplementary financial support for beginning farmers, organic producers, and regionally defined priority client groups. Despite its strengths, the program also faces challenges, including supporting the professional development and integration of new advisors, balancing service delivery with administrative demands, and ensuring all potential clients are aware of the program. Quebec’s experience shows how targeted public investment in advisory services can foster both economic resilience and environmental progress.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 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".