Characterizing Agroecology in North Africa, a Review of 88 Sustainable Agriculture Projects
Bibliographic record
Abstract
Agroecology refers to the greening of agrosystems with the mobilization of ecosystem services in order to limit exogenous inputs, enhance biodiversity and moderate the exploitation of natural resources. Agroecological practices offer pathways for transformation and transition not only of agricultural systems but of entire food systems. Through its objectives, agroecology aims at both sustainable land management and the strengthening of the livelihoods of producers and rural people and thus contributes to the fight against desertification. Currently, there is little scientific literature on the characteristics of agroecology in the Maghreb region. Several studies provide important information but they do not allow drawing up a global panorama of agroecology in the region. The proposed article highlights general characteristics of agroecology in North Africa from a review of 88 sustainable agriculture projects, which it analyzes, through an inventory of agroecological practices supported by these projects, from the frameworks of the High-Level Panel of Experts on Food Security and Nutrition, 2019, on the principles of agroecology and the transition levels approach developed by Gliessman and fellows since 2007. The results show (i) differences in the observed practices depending on the agrosystems and (ii) predominant common practices across these diverse agrosystems; (iii) significant evolution in these practices over time. The majority of the agroecological innovations identified are at the plot and farm scales, with the exception of those found in oasis and mountain agrosystems, where practices integrate the scales of the territory and value chains in a more complete way.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".