Toward Alternative Food Systems Development: Exploring Limitations and Research Opportunities
Bibliographic record
Abstract
In recent years, interest in alternative food systems (AFS) has grown both in the popular imagination and in the academic literature. The literature is rife with justifications (or hopes) for the continued and necessary expansion of AFS in the face of unsustainable conventional food provisioning. Within the next five years it will be important to determine how to make alternatives more stable in order for them to play a more prominent role in battling the food insecurity and other social and economic challenges equated with agro-industrial foods. The goal of this commentary is to demonstrate some highly context-specific challenges and possible research trajectories in both the global South and the global North. We argue that in the global South more robust data collection can strengthen local food systems and traditional foods research, while in the global North, food skills and food literacy research may be important for scaling up and making alternative food systems more stable without compromising important social and economic ideals.
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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 | 0.002 | 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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".