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Record W2906266039 · doi:10.32920/ryerson.14655966

Stories, unsung : using music theatre to empower isolated families

2021· preprint· en· W2906266039 on OpenAlexaffabout
Catherine Moher

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsToronto Metropolitan UniversityEducation and Early Childhood Development
Fundersnot available
KeywordsMusicalInclusion (mineral)Grounded theorySocial exclusionSocial changeSociologyPsychologyGender studiesSocial psychologyPublic relationsVisual artsPolitical scienceQualitative researchArtSocial science

Abstract

fetched live from OpenAlex

This study examines the impacts of a musical social theatre program entitled Stories, Unsung. The findings are based on the experiences of one group who participated in this program in Calgary, AB (N=8). This study uses a grounded theory and design to explore how useful musical social theatre can be in reducing the social exclusion of marginalized people. Findings indicate two factors are critical in enhancing the social inclusion of those who are isolated: 1) a change in understanding of self and 2) a change in the relationships with others. Stories, Unsung was successful in changing the participants understanding of self and others both critical elements in removing the barriers associated with social exclusion. It is recommended that practitioners working with families in family support programs consider musical social theatre as an effective strategy to engage those families who are socially excluded. Implications for future policy development and research are discussed.

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)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.003
Scholarly communication0.0020.002
Open science0.0010.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.108
GPT teacher head0.395
Teacher spread0.288 · 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

Citations1
Published2021
Admission routes2
Has abstractyes

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