Bibliographic record
Abstract
Purpose The purpose of this paper is to explore the perceived causes of lifestyle and weight changes among first-generation East/Southeast Asians and Hispanics after resettlement in Canada. Design/methodology/approach Semi-structured interviews with study participants (n=100) and local health professionals (n=6) were conducted. Prominent response themes were identified through a content analysis. Findings The most common theme was the exposure to an obesogenic environment, such as the more pervasive diffusion of unhealthy food options. Hispanic participants were more likely to report the acquisition of unhealthy food practices and struggled more to maintain their traditional food habits. Time constraints, mostly due to working long hours, were the second most common theme, as participants had little time for making healthier lifestyle choices. The cold weather was considered as a contributor to obesity-leading behaviors and mood disorders. Hispanic respondents were more likely to describe settlement-induced psychological stressors and often compensated feelings of depression and isolation by eating emotionally and increasing the consumption of comfort foods. Weight increases were more likely within the first five years of arrival. Practical implications Preventive efforts should include social integration strategies to counter depression, and provide recommendations on feeding times and sleeping habits. Interventions should pay particular attention to Hispanics and recent newcomers. Originality/value This study enhanced the understanding of the causes of obesity disparities in Canada by suggesting that the higher prevalence of overweight and obesity among Hispanics may be due to their particular risk of unhealthy dietary and mental health transitions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".