Defining food well-being from the perspective of young Canadian consumers: an exploratory study
Bibliographic record
Abstract
Food well-being (FWB) is fundamental for consumers' overall well-being. Previous studies have explored FWB through five domains (food socialization, literacy, marketing, availability, and policy) or food-related concepts (e.g., food pleasure, healthiness, and satisfaction). However, the understanding of FWB is limited due to two main issues: (1) the absence of a clear definition and reliable measurement tools for this multifaceted and multidisciplinary phenomenon, and (2) the tendency of studies to focus on individual dimensions rather than examining it as an integrated whole, making it difficult to understand how these dimensions are interconnected. To address these gaps, a qualitative exploratory study was conducted with young Canadian consumers using a focus group and 15 individual interviews. A directed content analysis revealed a disconnect between consumer perceptions and the existing definition of FWB. This study makes three key contributions to understanding FWB: first, it provides a deeper insight into FWB conceptualization by identifying new themes within its domains. These include: (1) food socialization, shaped by family, peers, and meal traditions; (2) food literacy, encompassing both conceptual and procedural knowledge, as well as individual goals; and (3) food marketing, shaped by the impact of marketing activities (the 4Ps) on food experiences. Second, this study presents a comprehensive framework that illustrates the interconnections among FWB domains. It highlights, for example, how food socialization influences food literacy, the interactions between food literacy and food marketing, and the role of policy in shaping FWB. Third, it offers practical implications for enhancing FWB in contemporary consumer society.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.018 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".