The role of social engagement and identity in community mobility among older adults aging in place
Bibliographic record
Abstract
UNLABELLED: The purpose of this study was to understand how neighbourhoods - as physical and social environments - influence community mobility. Seeking an insider's perspective, the study employed an ethnographic research design. Immersed within the daily lives of 6 older adults over an 8-month period, auditory, textual, and visual data was collected using the "go-along" interview method. During these interviews, the researcher accompanied participants on their natural outings while actively exploring their physical and social practices by asking questions, listening, and observing. Findings highlight a process of community mobility that is complex, dynamic and often difficult as participant's ability and willingness to journey into their neighborhoods were challenged by a myriad of individual and environmental factors that changed from one day to the next. Concerned in particular with the social environment, final analysis reveals how key social factors - social engagement and identity - play a critical role in the community mobility of older adults aging in place. IMPLICATIONS FOR REHABILITATION: Identity and social engagement are important social factors that play a role in community mobility. The need for social engagement and the preservation of identity are such strong motivators for community mobility that they can "trump" poor health, pain, functional ability and hazardous conditions. To effectively promote community mobility, the social lives and needs of individuals must be addressed.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| 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".