Relationships Between Neighborhood Social Capital and The Occurrence of Outdoor Falls in Canadian Older Adults: A Multilevel Analysis
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to examine whether neighborhood-level social capital is a risk factor for falls outside of the home in older adults. METHODS: Health questionnaires were completed by community-dwelling Canadians aged +65 years living in Kingston (Ontario) and St-Hyacinthe (Quebec), supplemented by neighborhood-level census data. Multilevel logistic regression models with random intercepts were fit. Variations in the occurrence of falls across neighborhoods were quantified by median odds ratio and 80% interval odds ratio. RESULTS: Between-neighborhood differences explained 7% of the variance in the occurrence of falls; this variance decreased to 2% after adjustment for neighborhood-level variables. In the fully adjusted models, higher levels of social capital increased the odds of falls by almost 2 times: (odds ratio [OR] = 2.10, 95% confidence interval [CI] = [1.19, 3.71]). DISCUSSION: Living in neighborhoods with higher levels of social capital was associated with higher risk of falling in older adults, possibly through more involvement in social activities.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 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".