Meals in the melting-pot: Immigration and dietary change in diversifying cities
Bibliographic record
Abstract
Changes in diets and food practices have implications for personal and planetary health. As these implications have become more apparent, dietary change interventions that seek to promote healthy and sustainable transitions have proliferated, and the processes and drivers of dietary change have come under increasing scrutiny. In particular, dietary acculturation has been recognised as a driver of dietary change in the context of immigration to expanding, cosmopolitan cities. However, research has largely focused on changes in the diets of immigrants and ethnic minorities. In contrast, this study contributes to our understanding of the process of dietary acculturation among the largest population groups in Vancouver, Canada - Chinese- and European-Canadians - in the context of the rapid diversification of the population and food environments in this city. This is done through the analysis of descriptive and contextualised interview and observational data, and a focus on social practices. These data show that food practices, particularly in cosmopolitan urban contexts, are constantly in flux, as diverse ethnic groups come into contact, and new generations develop their own hybrid food cultures. By demonstrating and theorising this process of dietary acculturation, this research offers insights how cultural interactions relate to dietary transitions. It presents an exploratory model for considering how food practices change through dietary acculturation, which is relevant to the design of interventions that aim to support healthier and more sustainable dietary transitions.
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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 | 0.000 | 0.000 |
| 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".