Healthy Aging in Place: Supporting Rural Seniors’ Health Needs
Bibliographic record
Abstract
PurposeTo examine the key determinants that support healthy aging in rural communities.SampleForty- two participants aged 65 and older were recruited from two rural communities in Saskatchewan, Canada.Methods Using an ethnographic methodological approach, data was collected through semi-structured interviews, field notes and participant observation notes. Cantor’s (1989) Social Care Model was used as the theoretical framework for exploring the supports that facilitate rural healthy aging.Findings Healthy aging among rural seniors extends significantly beyond access to physicians and formal health care. Eight key themes related to healthy aging were identified: housing; transportation; healthcare; finances; care giving; falls; rural communities; and support systems.ConclusionsWhile there is evidence of poor health among rural seniors, little research has examined healthy aging or the determinants that facilitate healthy aging in rural communities. In addressing rural seniors’ health needs, this study provides a fundamental basis for developing effective interventions and innovative public policy options to support rural healthy aging.Keywords: Rural Health, Social Support, Rural Aging, Public Policy, Disparities
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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".