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Record W4392348445 · doi:10.15845/voices.v24i1.3861

Global Perspectives on Addressing Systemic Issues in Music Therapy Curricula and Healthcare

2024· article· en· W4392348445 on OpenAlexaff
Amy Clements-Cortés, Melissa Mercadal-Brotons, Hakeem Leonard, Vivian Chan, Gro Trondalen, Tao-Deva Stingl, Thomas Stegemann, Cláudia Regina de Oliveira Zanini

Bibliographic record

VenueVoices A World Forum for Music Therapy · 2024
Typearticle
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMusic therapyCurriculumHealth careSociologyNursingPsychologyMedicinePsychotherapistPolitical sciencePedagogy

Abstract

fetched live from OpenAlex

The discipline of music therapy is practiced differently across the globe and over the years, in all regions of the world, the number of music therapy training programs has expanded. As such, there is a need to reflect on the differences between education and training programs, which vary according to the local culture, educational needs, theoretical background, and scope, among others. Music therapists work in a variety of environments including hospitals, community centres, regular or special education schools, speciality clinics, private practice, and long-term care homes, etc. Music therapists are tasked with navigating policies in their workplaces and balancing the needs of their clients/consumers/service users. This article written together by educators and a student aims to present brief highlights of the work of the authors whose collaboration resulted in a presentation at the European Congress of Music Therapy in June 2022. This presentation focused on the challenges and issues faced by the discipline of music therapy and health in general, based on the analysis of systemic issues in education and training, social issues, and significant issues such as multiculturalism, equity, and race around the world. These were identified as important issues for the authors who desired to raise awareness on these topics to further open ongoing dialogue. Our aim is to contribute to the establishment of dialogues between music therapy educators, allied health professionals, researchers, and students for the implementation of new courses and the updating of existing programs, expanding views on possible music therapy interventions in contemporary times.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.843
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.076
GPT teacher head0.400
Teacher spread0.325 · 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 designNot applicable
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

Citations4
Published2024
Admission routes1
Has abstractyes

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