Using agroecology to stimulate the greening of agriculture in China: a reflection on 15 years of teaching and curriculum development
Bibliographic record
Abstract
Even though worldwide research and teaching in Agroecology blossomed in the 1980s, until recently, the development of Agroecology in China has been constrained by technical, cultural and economic considerations. The delay in the assimilation of Agroecology, as a science, a practice and a movement, has resulted in the discipline of Agroecology in China lacking the holistic, interdisciplinary approaches needed to respond to current global and regional agricultural challenges. There is a need to redefine Agroecology both as a critical discipline and as a pedagogical approach. By using an ecology-oriented systematic approach to integrate education and research, a reframed Agroecology is proposed; this is based on a re-imagined, holistic consideration of the hierarchy of agroecosystems. The practical experience of a 15-year international team-taught Agroecology education programme among participants from Canada and China has helped refine disciplinary classifications, both from horizontal and vertical hierarchies. There are evolving impacts of this experiment in Sino-Canadian cooperation in Agroecological research and education; they include a new generation of highly trained agroecologists prepared to act across inter-related disciplines; the alignment of Chinese universities to international agricultural curricula and a better- informed policy-making process towards greening agriculture in China.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".