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Record W4387105915 · doi:10.36922/ijps.383

Re-conceptualizing music education in the older adult life course: A qualitative meta-synthesis

2023· article· en· W4387105915 on OpenAlexaff
Tuulikki Laes, Andrea Creech

Bibliographic record

VenueInternational Journal of Population Studies · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsMcGill UniversityCentre for Interdisciplinary Research in Music Media and Technology
Fundersnot available
KeywordsLifelong learningMusic educationLife course approachThe artsPsychologyAdult educationSociologyPedagogyGerontologyPolitical scienceDevelopmental psychologyMedicine

Abstract

fetched live from OpenAlex

The Seoul Agenda by UNESCO has set goals to develop arts education, ensuring that learners from all social backgrounds have lifelong access to arts education in a wide range of community and institutional settings. However, the purpose of lifelong learning for individuals beyond labor-market age has been largely overlooked, making it challenging to convince institutions, funders, and policymakers of its worth. The value accorded to the complex forms of lifelong learning in later life and the widely recognized health impacts of music on aging body and brain are the principal considerations to take into account when studying the effects of music education on older adults. In this study, we address the state-of-the-art research concerning older adults and music education in studies published in major peer-reviewed music education journals since the Seoul Agenda by UNESCO. We present the findings from a systematic literature review, followed by a qualitative meta-synthesis, focusing on the values, beliefs, and key concepts conveyed in the included studies. The findings of this study indicate that older adults are often portrayed narrowly and stereotypically, corroborating the issues in the sociology of aging. Our study highlights insights into the conceptualizations of music learning and participation in later life course and what these might mean for the policy and practice of later-life music education and the educational opportunities for older adults more broadly.

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)0.001
metaresearch head score (Gemma)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.197
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0010.000

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 head0.316
GPT teacher head0.437
Teacher spread0.121 · 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

Citations9
Published2023
Admission routes1
Has abstractyes

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