Social inequalities in household food availability and wellbeing among newcomer adolescents in Canada: A Health Behaviour in School-Aged Children 2017/2018 Study
Bibliographic record
Abstract
Abstract Purpose:This study sought to assess how hunger and wellbeing differ among newcomer adolescents versus non-newcomer adolescents in Canada and the associations between these factors. Methods:This study represents results from a proportional sample of 21,750 adolescents in Canada recruited through the HBSC-Canada study 2017/2018 cycle. It used measures of migration status, the WHO-5 measure of wellbeing, hunger, and family support factors in regression models to estimate cross-sectional associations between migration status and hunger, and wellbeing while controlling for covariates and the nested nature of the data. Results:Approximately 32.1% of the sample were newcomers and newcomers were more likely to be hungry (20.4%) compared with non-newcomer adolescents (15.5%). The regression analyses confirmed this association and also showed that newcomer adolescents also reported lower wellbeing compared with non-newcomer adolescents. Further analyses showed that among hungry adolescents, non-newcomers reported lower wellbeing than newcomer adolescents in Canada. Conclusion:Although newcomer adolescents report overall lower wellbeing and more hunger with non-newcomers; when hungry, newcomers report higher wellbeing than their non-newcomer peers. This resilience to hunger may be explained by living in other adversity (i.e., more household deprivation, less family supports) which were living conditions found among newcomer adolescents in this study.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| 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".