Trends and patterns of life satisfaction and its relationship with social support in Canada, 2009 to 2018
Bibliographic record
Abstract
The present study aims to explore the trends and patterns of life satisfaction in Canada from 2009 to 2018 and to examine changes in the associations between social support and life satisfaction over time. Data were from ten annual Canadian Community Health Surveys (CCHS). Each survey represents 97% of the Canadian population. Point estimates and 95% confidence intervals (CIs) of life satisfaction were calculated at the population level. Generalized linear regression was used to explore the relationship between life satisfaction and social support both nationally and in different population subgroups. The annual life satisfaction score gradually increased both at national and provincial levels from 2009 to 2018. Individuals who were women, aged between 12 and 19 years, living in rural areas, were most satisfied with their lives. There was a positive correlation between social support and life satisfaction for the provinces and the study years for which information on social support was available. Our findings suggest strengthening social support could be a public health target for promoting greater life satisfaction. Timely availability and analysis of life satisfaction and social support data could better inform policy and promote wellbeing at a population level.
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 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 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".