Embedding global sustainable development goals in local agroecology initiatives: experiences from China
Bibliographic record
Abstract
As part of sustainable agricultural innovations and the alternative food movement, agroecology provides important tools to achieve the sustainable development goals (SDGs). Yet very few existing studies have explicitly addressed their linkages. Synergies among the SDGs are often examined at the national level, overlooking nuanced opportunities revealed by small agroecology initiatives at the local scale. Based on literature review, field visits and semi-structured interviews with farms and relevant organizations in China, this research investigates how locally embedded agroecology practices lead to advancement of multiple SDG targets and facilitate the synergies among the SDGs. It also highlights their motivations, achievements, and challenges. We argue that the technocentric metrics of SDGs underappreciate the application of traditional knowledge and small-scale low-tech innovations. By bringing visibility to low-tech and small agroecology initiatives, this paper advocates for stronger inclusion of grassroots agroecology initiatives in SDG discussions among researchers and policy makers.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".