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Record W2787304571 · doi:10.1177/1471301217752209

Making a university community more dementia friendly through participation in an intergenerational choir

2018· article· en· W2787304571 on OpenAlexfundno aff
Phyllis Braudy Harris, Cynthia Anne Caporella

Bibliographic record

VenueDementia · 2018
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
FundersAlzheimer Society
KeywordsDementiaChoirPsychologyCohortFeelingStigma (botany)EmpowermentFocus groupGerontologyDevelopmental psychologyPsychiatryMedicineSocial psychologySociologyPedagogyDisease

Abstract

fetched live from OpenAlex

A dementia friendly community is one that is informed about dementia, respectful and inclusive of people with dementia and their families, provides support, promotes empowerment, and fosters quality of life. This study presents data from four cohorts of undergraduate college students and people with dementia and their family members, using an intergenerational choir as the process through which to begin to create a dementia friendly community. This was accomplished by breaking down the stereotypes and misunderstandings that young adults have about people with dementia, thus allowing their commonalities and the strengths of the people living with dementia to become more visible. Data were gathered for each cohort of students through semi-structured open-ended questions on attitudes about dementia and experiences in the choir, collected at three points over 10 weeks of rehearsals. Data about their experiences in the choir were collected from each cohort of people with dementia and their family members through a focus group. Results across all four cohorts showed in the students: changed attitudes, increased understanding about dementia and the lived experience, reduced dementia stigma, and the development of meaningful social connections. People with dementia and their family members expressed feelings of being part of a community.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.081
GPT teacher head0.407
Teacher spread0.326 · 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 designObservational
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

Citations45
Published2018
Admission routes1
Has abstractyes

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