Bibliographic record
Abstract
This second volume of the country reports series enlarges the documentation, analysis, and development of agroecology in Europe, and provides examples of implementation in different countries. The 11 countries studied within this volume show somewhat similar results as found in with the first 13 countries mapped in volume 1. There are quite contrasted situations regarding the development of agroecology in different countries. In some countries many existing initiatives with a direct or indirect link to agroecology and some of its principles can be document, whereas the implementation of agroecology or the use of the concept and approaches are still limited in other countries. This does not mean that some countries are better than others, only that agroecology evolves distinctly through the history of agriculture and foods systems as well as<br/>the policy framework.<br/><br/>Diverse visions, definitions, and use of the concept of agroecology exist in different countries, but a gradual convergence can be observed. Only a few clearly defined educational and training programmes can be documented for the majority of the countries analysed, some of these already exist for years. Dedicated research units, programmes, and projects with the name agroecology are limited in most countries, but they are growing in numbers over the last years. A lot of research related to agroecology is carried out in many countries without being explicitly on agroecology. Living labs are not much known, even less so in relation to agroecology, however, their numbers are increasing in the past years, but in most cases without explicitly referring to agroecology.<br/><br/>In addition to expanding the body of knowledge on initiatives linked to agroecology, this volume illustrates what needs to happen for the development of agroecology in Europe. Yet more countries are being mapped for following volumes of this series to give broad analysis and enhanced insights for the future development of agroecology in Europe.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 0.002 |
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; both teacher heads agree on what is shown here.
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".