Creating New Urban Spaces of Sustainability and Governmentality: An Assessment of the Development of a Food and Urban Agriculture Strategy for Edmonton, Canada
Bibliographic record
Abstract
Abstract Purpose The purpose of this chapter is to explore the potential of urban agriculture (UA) as a tool for advancing urban sustainability. Methodology/approach The chapter is based on participatory action case research focused on the development of an urban food policy in Edmonton, Canada from 2008 to 2013. Three data gathering techniques were employed: participant observation, semi-structured interviewing, and document analysis, and the data was analyzed using a grounded theory approach that including coding for themes and triangulation. We also draw on the work of critical sustainability scholars to outline the propensity for innovative work on local food initiatives to follow the same development path as many urban sustainability initiatives that foreclose political debate and reinforce the status quo. Findings The research data reveals that despite initial progressive changes in municipal policy, promising innovative food system planning, in the end Edmonton’s city council were largely driven by a development agenda. Originality/value In discussing both the successes and remaining challenges for Edmonton, this case study offers instructive lessons for many municipalities about key factors required for moving urban sustainability forward, specifically with respect to capitalizing on the innovative integrative functions of food for organizing communities and building capacity but also in moving beyond technocratic systems of management and planning to advance a paradigm shift toward building urban food security.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.015 | 0.007 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".