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Record W2796217041 · doi:10.1177/1359457518759960

Building community through song: The therapeutic hospice choir

2018· article· en· W2796217041 on OpenAlexaff
Jane Gosine, Ray Travasso

Bibliographic record

VenueBritish Journal of Music Therapy · 2018
Typearticle
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsChoirSingingPsychosocialMusic therapyNursingPsychologySocial workMedicinePsychotherapistPedagogyPolitical science

Abstract

fetched live from OpenAlex

Music enables us not only to reflect upon the world in which we live but also to become active agents in creating and shaping it and ourselves. The Treehouse Choir is an innovative, therapeutic programme open to all adult service users and staff at one of the East Anglia’s Children’s Hospices. The target group of the choir membership focuses primarily on the mothers of children receiving care at the hospice and bereaved mothers. The choir addresses the need for psychosocial support for families as they face the challenges of caring for a child with life-limiting and complex health conditions, as well as families mourning the loss of a child. This article analyzes data collected from questionnaires and interviews referring to the emotional, psychological and social benefits of participation in the choir. It examines how singing in the choir serves as a means through which individuals form a community built on shared life experiences, bridging boundaries between service provider and service user, creating a means of self-expression, and breaking down barriers to enable new lines of communication within a non-threatening environment. It also examines the role of public performances in promoting greater awareness of the services provided by the hospice.

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)0.003
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.919
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.107
GPT teacher head0.378
Teacher spread0.271 · 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 designOther design
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

Citations8
Published2018
Admission routes1
Has abstractyes

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