Évaluer la durabilité des élevages en Agriculture Biologique et communiquer sur leurs externalités positives
Bibliographic record
Abstract
The Saffré basin is a drinking water catchment area classified as prioritary due to pesticide residues in the water. In response to this problem, local authorities have set a ‘zero pesticides’ target for 2040. A quarter of organic farms are already pesticide-free. However, the long-term viability of these farms is threaten by a crisis in demand for organic produce. In this context, eight organic farmers have joined forces to communicate the benefits of their practices and raise awareness among a wide range of audiences of the links between agriculture, health, food and the environment. Sustainability assessments were carried out on these farms using the IDEA4 method. These demonstrated the very high level of agro-ecological sustainability of the farms, linked to very low impacts on health and ecosystems. At the same time, an approach combining participatory workshops, document review and surveys has led to the design of a communication initiative, scheduled for this autumn in the form of a farm visit to which local elected representatives will be invited. The aim will be to raise awareness of the benefits of organic farming in preserving water resources, and of the need for public support in a difficult context. Recommendations were drawn up on the content and form of the event to maximise its impact. Other actions to raise awareness of the impact of food practices on agriculture, the environment and health, targeting school audiences or consumers, are envisaged.
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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 | 0.014 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".