Canadian food retailers' reasons for adopting the Eat Well Campaign (2013–14) - A qualitative study
Bibliographic record
Abstract
Background In 2013, Health Canada (HC) launched the Eat Well Campaign (EWC), a year-long social marketing campaign focusing on food skills, in collaboration with stakeholders including food retailers. Given that adoption of an innovation depends, in part, on its characteristics, the purpose of this study was to explore the characteristics of the innovation (i.e. EWC) that were reported by food retailers as reasons for collaborating with HC. Methods Semi-structured phone interviews were conducted with Canadian food retailers (n = 8) who were involved in the campaign. Interviews were conducted during and following the campaign. Thematic content analysis of interviews transcribed verbatim was performed by three coders assisted by NVivo10 software. An a priori codebook based on Rogers’ Diffusion of Innovations decision process model was used. Results Preliminary findings show that the main perceived relative advantages of participating in the EWC were: enhanced positive organizational image and credibility in terms of partnering with a credible organization like HC, providing relevant information to their customers related to healthy eating, and having an opportunity to collaborate with HC and other retailers. The majority of retailers perceived that the EWC fit with their organization’s mission and practices as well as with their customers’ needs. The EWC was not seen as complex, and therefore not a barrier for its adoption. Conclusion Preliminary analysis identified relative advantages, compatibility and low-complexity as being the key characteristics of the innovation related to the adoption of the EWC by food retailers. These findings will be useful to understand the innovation-decision process and the reasons for private-public partnerships in public health nutrition. Key messages This study identifies key attributes of the innovation (i.e. a healthy eating campaign) related to its adoption by food retailers These findings contribute to a better understanding of collaborations between the retail food industry and public health organizations
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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 | 0.028 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".