From Adoption to Adaptive Learning: The Need for Farmer-Centric Soil Health Extension and Education Evaluation
Bibliographic record
Abstract
In the Canadian agri-food system, there is a growing and perceived need to evaluate soil health from the perspective of farmers. Ultimately, farmers determine if and how they adopt inputs including technologies and expert advice. Adoption is a term often used to refer to a farmer’s decision to change a management practice. This is however, a limited understanding of the term, which may not appreciate the wholeness of understanding and adapting a management practice on-farm. This paper uses a meta-analysis methodology to explore the need for farmer-centric soil health extension and education assessment. The studies reviewed suggest that the social elements of soil health may be more relevant to understanding sustainability transitions than a focus on the adoption of specific management practices alone. An understanding that gives weight to the social influences that guide a farmer’s adaptive management decisions, including practices of leading or learning-by- doing, self-awareness, and the role of social interactions within those practices and interventions. Exploring the ‚social side of soils, comes at a time when the Ontario strategy for soil health entitled ‚New Horizons‚ has set out a framework in which to support farmer-centric soil health extension and education. Funding: NSERC CREATE Climate Smart Soils
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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 | 0.001 | 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".