Building sustainable communities through alternative food systems
Bibliographic record
Abstract
Food provides a meaningful lens to create and build more sustainable communities. Given the challenges currently facing humanity it offers a shared basis for transformation. It can act as a platform for social equity, personal well-being, ecological resilience and robust economies. Through food, we have the capacity to tackle climate change, water quality and quantity degradation, the global diabetes crisis, and gross social inequity. While acknowledging that each community food system is as unique as the space/place where it emerges, there are some factors that seem to increase levels of sustainability. The proposed chapter will extend earlier theoretical work on sustainable food systems and assess existing frameworks in light of empirical work through a selection of case studies in Ontario, Canada. These case studies are grounded in work from six universities and represent a scan of over 200 projects in the province. Each case study will be assessed through the lens of complex adaptive systems theory with a view to understanding more about the role of the principles derived from chaos and complexity theory including diversity, connectivity, self-organization, nested hierarchies and iterative feedback loops.
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.
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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".