“We need more things for us”: Being low income and underoccupied in older age
Bibliographic record
Abstract
BACKGROUND.: Low-income older adult populations have increased vulnerability to occupational engagement barriers and poor health outcomes while aging in community settings. PURPOSE.: The purpose of this study was to examine the relationship between community navigation and well-being for low-income older adults. METHOD.: = 10) were recruited for this multimethod observational cohort study, which employed GPS data, measures of well-being, and semistructured interviews across 12 months. Grounded theory processes were followed to analyze and integrate the qualitative, quantitative, and spatial data. FINDINGS.: Findings were three patterns of community navigation. In particular, patterns of being chronically underoccupied were noted for this low-income population. Specific place-based challenges are explained along with strategies used to mitigate these challenges. IMPLICATIONS.: Supporting community navigation, especially social interaction opportunities, can maximize well-being; and older residents' occupational participation may be unnecessarily curtailed by geographic, economic, and social factors beyond their control. Community navigation strategies should be considered holistically by occupational therapists as part of interventions supporting aging in place.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".