Could an Ecosystem Perspective Support the Creation of a Nonprofit Food System? A Theoretical Exploration of the Possibilities
Bibliographic record
Abstract
Although food has been designated a human right, most countries do not provide the means for their citizens to exercise that right. As a result, food is treated as a commodity and sold for a profit to those who can afford it, leaving millions of people undernourished as food prices rise. One solution to this problem is the establishment of a nonprofit food system. A daunting prospect—how could this be carried out? One potentially useful approach that is increasingly being applied in social economy scholarship involves an ecosystem perspective, which takes account of not only social economy organizations but also the wider environments in which they operate. Could such a perspective support the creation of a nonprofit food system? This article explores the possibilities offered by applying an ecosystem perspective to a nonprofit food system. After providing some preliminary background information on food systems, it introduces the ecosystem perspective and affirms that it can indeed support the creation of a nonprofit food system.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.025 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".