Trade‐offs in the performance of alternative farming systems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Numerous alternative farming systems are proposed as solutions to the sustainability challenges of today's conventional farming systems. In this paper, we review the production, environmental, and socioeconomic performance of three widely discussed and promoted alternative farming systems—organic, smallholder, and urban agriculture. We show that both organic and smallholder agricultures have some benefits, but also entail important trade‐offs; organic has environmental benefits, and also livelihood, health, and nutritional benefits for producers and consumers, but is hampered by lower yields and higher prices. Smaller farms have higher yields and host higher biodiversity, but are hampered by lower incomes to farmers. Urban agriculture can take some pressure off rural landscapes, provide nutritional benefits to the urban poor, and engage urban dwellers in addressing food system challenges, but it simply cannot scale up to be a substantial solution in and of itself. We suggest that instead of focusing on alternative systems, we should identify pathways to sustainable farming for all systems, reforming conventional systems where they perform poorly, and transitioning to alternative systems in contexts where they perform best.
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.
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) | 0.000 | 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 it