Envisioning a community food hub to support food security
Bibliographic record
Abstract
Objective: The objective of this community-based participatory action research (CBPAR) project was to gain an in-depth understanding of the needs, interest and opportunities that exist within a post-secondary institution with respect to supporting food security among students via a food hub. Methods: The project was undertaken on the campus of the University of British Columbia-Vancouver. The CBPAR approach included 4 phases: 1) information gathering, 2) relationship development, 3) implementation of the community engagement strategy, and 4) shareback of findings to the community. Results: Phase 1 identified key components that formed the research process including campus partners for relationship development (phase 2) and subsequent engagement through their networks (phase 3). Phase 3 included engagement of 62, 111, 156, and 154 students, who participated in facilitated dialogues, community meals, a survey and targeted survey, respectively. Food insecurity related experiences were prevalent, with 37% to 75% indicating they worried about running out of food in the last year. Over 90% of all survey respondents affirmed that they would access a community food hub (CFH). Preferences for the CFH were inclusion of emergency food access, community meals, and financial support and planning, while prioritizing foods that meet cultural needs, and a low cost grocery store within the CFH. Conclusion: There is a demonstrated need and desire among students for innovative approaches to support food security at a post-secondary institution. The process outlined may serve as a road map for other communities who are seeking to move beyond emergency food relief.
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 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 | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".