Social well-being of Canadian adolescents: A national socioecological analysis of individual, household, and living area correlates
Bibliographic record
Abstract
In an era of widespread online socializing, little is known about the conditions that shape adolescent social well-being, a key aspect of their overall well-being. Using a socioecological approach, this study examines the social well-being (SoWB) of Canadian adolescents and its individual, household, and living area correlates. SoWB is conceptualized as an individual-level outcome reflecting adolescents' appraisal of their social connections and how these relate to their overall well-being. High SoWB is operationalized as the intersection of strong community belonging and high life satisfaction. Data from the Canadian Community Health Survey (2015–2020; n = 23,980) were analyzed for adolescents aged 12–17. Environmental measures were developed using 2016 Census data to capture living area differences based on population density, housing characteristics, and transportation modes, as well as the proportion of youth in local populations. Individual data and environmental data were linked using geographic identifiers. Results showed that adolescents with higher odds of high SoWB were significantly more likely to report better general and mental health, be younger, live in larger households, and belong to middle- or high-income groups. Living area characteristics were also significantly associated with SoWB: adolescents living in Atlantic Canada, in rural or small-town areas with weak metropolitan influence, and in youth-dense areas had higher odds of high SoWB, even after adjusting for individual and household factors.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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".