The Physical, Mental, and Social Health of Middle-Aged and Older Adults Without Close Kin in Canada
Bibliographic record
Abstract
OBJECTIVES: We examine whether adults aged 45 and older lacking a partner and children are disadvantaged in terms of physical, mental, and social aspects of health. Then we test whether the importance of family structure for these outcomes varies by age, gender, and educational attainment. METHODS: We examine aging and social network modules from the Canadian General Social Survey to estimate associations between family structure and physical, mental, and social health, with the last measured as communication with relatives and friends, civic participation, and loneliness. RESULTS: Results show that middle-aged and older adults without partners have lower levels of physical and mental health and higher levels of loneliness than those with partners. Those without partners and children (the "kinless") interact less with relatives than those who have children but not partners, but more with friends, showing some substitution. In terms of civic participation, kinless middle-aged and older adults have significantly lower odds of this type of engagement than peers with close kin. Our interaction models find some differences by age, gender, and education, which vary by the outcome. DISCUSSION: Our results highlight some concerns about the well-being of kinless adults in Canada, especially as related to physical and mental health and two aspects of social health, loneliness, and civic participation. We find some substitution occurring, whereby middle-aged and older adults without family are interacting more with friends than comparable peers, but such substitution is marginal.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 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".