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Record W2315172569 · doi:10.1177/1359457516639549

The role, function and identity of music therapists in the 21st century, including new research and thinking from a UK perspective

2016· article· en· W2315172569 on OpenAlexfundno aff
Helen Odell‐Miller

Bibliographic record

VenueBritish Journal of Music Therapy · 2016
Typearticle
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsnot available
FundersCanadian Institute for Advanced Research
KeywordsMusic therapyIdentity (music)Perspective (graphical)Multidisciplinary approachDementiaPsychologyPsychotherapistMental healthMedicineAestheticsSociologyVisual artsSocial science

Abstract

fetched live from OpenAlex

This article examines the identity of music therapy and music therapists, focussing upon the United Kingdom as a case study, but also considering international trends. Milestones in the history of music therapy in postwar United Kingdom and professional development in the 21st century are discussed, drawing upon research and clinical practice. Research outcomes across different specialities indicate that music therapy should be widely available to many populations, such as for people with dementia, autism, stroke and mental health problems and so on. These advancements mean that music therapists need to be clear about their role and identity in both doing the work and communicating about it. The article celebrates advances in research, thinking and provision and emphasis collaboration across multidisciplinary groups through an overview of different identities.

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)0.012
metaresearch head score (Gemma)0.015
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: none
Teacher disagreement score0.026
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0100.031
Scholarly communication0.0240.014
Open science0.0010.014
Research integrity0.0080.006
Insufficient payload (model declined to judge)0.0040.001

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 head0.095
GPT teacher head0.381
Teacher spread0.286 · 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

Citations8
Published2016
Admission routes1
Has abstractyes

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