Intergenerational Practice in the Community—What Does the Community Think?
Bibliographic record
Abstract
The many changes that occur in the lives of older people put them at an increased risk of being socially isolated and lonely. Intergenerational programs for older adults and young children can potentially address this shortfall, because of the perceived benefit from generations interacting. This study explores whether there is an appetite in the community for intergenerational programs for community dwelling older adults. An online survey was distributed via social media, research team networks, and snowballing recruitment with access provided via QR code or hyperlink. Semi-structured interviews were undertaken with potential participants of a pilot intergenerational program planned for the Eastern Suburbs of Sydney, Australia in 2020. The interviews were thematically analyzed. Over 250 people completed the survey, and 21 interviews took place with older adults (10) and parents of young children (11). The data showed that participants were all in favor of intergenerational programs, but there were different perceptions about who benefits most and how. The study highlighted considerations to be addressed in the development of effective and sustainable intergenerational programs. For example, accessing people in the community who are most socially isolated and lonely was identified as a primary challenge. More evidence-based research is needed to support involvement of different cohorts, such as those who are frail, or living with physical or cognitive limitations.
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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 | 0.014 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.016 |
| Scholarly communication | 0.011 | 0.015 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.006 |
| 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".