Integrated Sustainability Planning and Local Food Systems: Examining Areas of and Gaps in Food Systems Integration in Community Sustainability Plans for Municipalities across British Columbia
Bibliographic record
Abstract
No “one size fits all” approach exists for local sustainability and food systems planning. Such planning must balance needs for being both comprehensive and place-based. The current study explores this tension by examining Integrated Community Sustainability Plans (ICSP) developed by municipalities in British Columbia (BC), Canada. The research examines items and actions related to food systems (focusing on agriculture and food production) in the ICSPs of municipalities in different regions across BC to (1) identify how municipalities “integrate” food systems with other sustainability objectives, (2) elucidate how place and geography influence integrated planning, and (3) reveal gaps in integrated approaches to developing local food systems. The study employs document analysis and thematic coding methodology. The results indicate that common areas of food systems integration in ICSPs include local economy and education. Many plans outline goals for bolstering local food economies and building local food capacity through community participation and engagement. Findings also show how foci and approaches for developing sustainable food systems vary by region. The study elucidates how food systems are integrated within place-based sustainability plans as well as reveals gaps that local governments can address when adopting and implementing integrated sustainability plans for improving food systems.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".