The potential of local food systems in North America: A review of foodshed analyses
Bibliographic record
Abstract
Abstract Foodshed analysis provides a way to assess the capacity of regions to feed themselves. While dozens of foodshed analyses have been completed across North America, they have not been systematically analyzed. This paper reviews 22 foodshed analyses completed in the USA and Canada between 2000 and 2013. The criteria used to evaluate the foodshed studies are authorship/type of publication, spatial extent, goals and questions, methods and data sources for assessing consumption and production, analysis of pathways from production to consumption and findings. Similarities and differences, along with strengths and weaknesses, are identified. Together, the foodshed studies indicate significant opportunity for food system relocalization across North America. Foodshed studies are a potentially powerful tool for policy analysis and planning. A future research agenda for foodshed studies is identified, including addressing data gaps and establishing more standardized models for evaluating production, consumption and pathways.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".