PSYCHOSOCIAL WELL-BEING, RELATIONSHIP STATUS, SEXUALITY, AND GENDER IN THE CANADIAN LONGITUDINAL STUDY ON AGING
Bibliographic record
Abstract
Abstract Social connection and support are vital components of later-life health; for many older people, much of this support comes from a spouse or partner. Existing research has shown that gender and sexuality are central to the effects of partnership, and thus the later-life psychosocial and mental health benefits of partnership also likely differ by these factors. Canadian Longitudinal Study of Aging (CLSA) participants were categorized according to gender and sexuality; we analyzed how the effects of relationship status differed across these categories. Several psychosocial and mental health outcome variables were tested, including depression symptoms, mood disorder, anxiety, self-rated health, social support, and social standing. Linear and ordered logistic regressions were conducted, adjusting for age and education. Married persons had lower depression scores (B=-2.20, p<.001), higher social support (B=21.49, p<.001), and subjective status (B=.61, p<.001) than other relationship categories. The differences themselves differed by gender and sexuality: lesbian/bisexual women were better overall and experienced less adverse impact (B=23.37, p<.001), while these had greater effects on gay/bisexual men (B=21.10, p<.001). Lesbian/bisexual women have greater social supports across relationship statuses, while gay/bisexual men have less social support if not partnered. Findings highlighted variable and gendered effects of relationship status and sexual orientation on psychosocial outcomes. Examining differential effects for gender and sexual minority groups is essential to inclusive gerontological research.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| 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".