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Record W3202798726 · doi:10.3390/socsci10100374

Intergenerational Practice in the Community—What Does the Community Think?

2021· article· en· W3202798726 on OpenAlexaff
Gail Kenning, Nicole Ee, Ying Xu, Billy L. Luu, Stéphanie Ward, Micah B. Goldwater, Ebony Lewis, Katrina Radford, Kaarin J. Anstey, Nicola T. Lautenschlager, Anneke Fitzgerald, Kenneth Rockwood, Ruth Peters

Bibliographic record

VenueSocial Sciences · 2021
Typearticle
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPsychologyPerceptionGerontologyDevelopmental psychologySocial psychologySociologyMedicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.236
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.192
GPT teacher head0.506
Teacher spread0.314 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations16
Published2021
Admission routes1
Has abstractyes

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