MétaCan
Menu
Back to cohort
Record W3014187714 · doi:10.1093/geroni/igz038.2761

THE EMERGENCE AND BENEFITS OF SOCIAL RELATIONSHIPS IN TWO COMMUNITY-BASED DEMENTIA CHOIRS

2019· article· en· W3014187714 on OpenAlexaff
André Smıth, Debra Sheets, Mary Clare Kennedy, Tara Erb, Ruth Kampen, Min Zhou, Chandra Berkan Hozempa, Stuart MacDonald

Bibliographic record

VenueInnovation in Aging · 2019
Typearticle
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsLonelinessReciprocity (cultural anthropology)FeelingDementiaChoirSocial isolationPsychologySocial capitalSocial psychologyDevelopmental psychologyGerontologySociologyMedicinePedagogySocial sciencePsychiatryDisease

Abstract

fetched live from OpenAlex

Abstract Community choir participation for persons with dementia (PwD) confers benefits to health and well-being, including the benefit of socializing which can reduce feelings of loneliness and social isolation. Using the concept of social capital, this study examines the degree to which two intergenerational Voices in Motion choirs facilitate the development of social relationships between PwD, caregivers, and high school students. Data collection involved interviews with 17 dyads of PwD and caregivers, completion of a social relationship questionnaire, and focus groups with a total of 29 high school students. The results show a gradual increase in the level of interactions between all participants, with students in particular interacting more frequently with PwD. Over time, trust and reciprocity emerged within the choirs as more people shared information about themselves. Students’ understanding of dementia changed over time as they learned to appreciate PwD as unique human beings with rich life stories and experiences.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.002
Scholarly communication0.0020.001
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.110
GPT teacher head0.391
Teacher spread0.281 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueInnovation in AgingSame topicMusic Therapy and HealthFrench-language works237,207