The distribution of hunger in Canadian youth
Bibliographic record
Abstract
INTRODUCTION: As a foundation for prevention, evidence is required to establish the contemporary distribution of hunger in Canadian adolescents. We present findings from a nationally representative survey of young Canadians on how perceived hunger is distributed demographically, socially and contextually. METHODS: A probability-based sample of 15 656 young Canadians aged 11 to 15 years who completed the 2017/18 cycle of the Health Behaviour in School-aged Children study was used. Descriptive statistics and multivariable regression analyses were used to profile the study population and the distribution of hunger attributed to "not having enough food at home." RESULTS: Overall, one in six (16.6%) survey participants reported experiencing hunger. There was a strong and significant correlation between low socioeconomic status and hunger (p $lt; 0.001 for the low and middle socioeconomic groups, compared to the high socioeconomic status group). Notably, 12.5% of participants with high levels of affluence also reported such experiences of hunger; however, this was not a statistically significant finding. Hunger was less frequently reported in older participants and in higher grade levels, with some level of significance. Regression analyses indicated that, within the sample, some demographic characteristics correlated with experiences of hunger: lower levels of affluence, identifying as male or nonbinary gender, long-term immigrant status, and identifying as Black, Latin American or mixed ethnicity. CONCLUSION: Clear disparities exist in the self-reported experience of hunger among young people in Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".