Urban agriculture: a social development tool : improving access to affordable, healthy food in a low-income area of Toronto, Canada
Bibliographic record
Abstract
This research paper is a systemic analysis of the Black Creek Community Farm (BCCF), a new large-scale urban agriculture project that takes place in a deprived area of Toronto, Canada. The Black Creek area faces poverty and is identified as one of the food deserts that exist in North America. The different partners involved in BCCF are aware of the important role the community has to play in order for the project to succeed and in order for it to improve access to healthy and quality food in the area. Within this preliminary context, Peter Checkland’s Soft System Methodology has been used to examine the situation in detail and assess its capacity to act as a social development tool. A combination of structured and spontaneous interviews as well as the technique of visioning allowed for the identification of what the community desires for future projected situations. This report suggests a number of possible next steps to be implemented, founded on the ideas collected, in order for the community to obtain ownership of the project and develop access to healthy quality food in the neighbourhood. Both BCCF and the research project faced some challenges that are discussed and situated within a wider context in order to better assess any opportunity of replicating similar actions in other cities.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".