New Dimensions in Agroecology for Developing a Biological Approach to Crop Production
Bibliographic record
Abstract
Summary Agroecology is emerging from the conceptual realm to become a significant discipline in North America and many parts of the world. We explore 10 dimensions of agroecology that are important in developing a more biologically-based science of agriculture: (1) a new philosophy of agriculture, (2) systems thinking, (3) local adaptation, (4) the non-crop biota, (5) crop autecology, (6) encompassing the agricultural landscape, (7) closing the materials cycle: crops, livestock and local or global cycling, (8) technology and ecology, (9) human ecology, and (10) the natural dimension. Agroecology deals with the applications of ecological principles in agroecosystems and it represents a logical response to shortcomings of conventional agriculture. Current crop production approaches fail to account for biological complexities of agro-ecosytems and the need to feed the world without jeopardizing the sustainability of its life support systems. A key strategy employed by agroecologists is to compare agroecosystems and natural ecosystems systematically, and attempt to integrate knowledge of natural ecosystems into agricultural practice. Through this process, traditional agronomy is elevated to agroecology.
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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 | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.027 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".