“They hold on tight to the healthy eating, we hold on tight to our food safety, and how do we bridge that?”: determinants of successful collaboration between food safety and food security practitioners in British Columbia, Canada
Bibliographic record
Abstract
Food safety and food security are two important public health sectors within Canada, which aim to address foodborne disease and food insecurity, respectively. While these sectors are often siloed within public health organizations, the actions of the two sectors often interact and conflict at the program level despite their common goal of improving population health. The objective of the present study was to identify determinants that influenced the success of collaboration between practitioners of the two sectors in British Columbia, to inform Canadian food policy. We inductively analyzed 14 interviews with practitioners working in the two sectors who had experience with successful collaboration. Data were interpreted in consultation with an inter-professional collaboration framework. Participants identified determinants at the systemic level, including the cultural, professional, educational, legislative, and political systems, which were often considered barriers to collaboration. Participants also identified determinants at the organizational level that influenced the success of collaboration between the sectors, including: the organization’s structure and philosophy, leadership, resources, and communication mechanisms. Finally, participants identified interactional determinants as ways to overcome existing barriers, including: willingness to collaborate, trust, communication, mutual respect, and taking a solutions-oriented approach. Practitioners working in food safety and food security can apply the interactional determinants identified in this study to mitigate existing barriers to collaboration and support more synergistic food policies.
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 | 0.017 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.033 | 0.012 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| 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".