MétaCan
Menu
Back to cohort
Record W4385331974 · doi:10.47513/mmd.v15i3.862

Culturally diverse music creation as a prototype for effective intercultural collaboration in health care

2023· article· en· W4385331974 on OpenAlex
Aaron J. Lightstone, Justin Gray, Bev Foster

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMusic and Medicine · 2023
Typearticle
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsHumber Polytechnic
Fundersnot available
KeywordsMusicalProcess (computing)Health carePsychologyIntercultural communicationSociologyPublic relationsPedagogyPolitical scienceComputer scienceVisual artsArtLaw

Abstract

fetched live from OpenAlex

In mid-2018, the authors[1] were contracted by the YYZ Foundation[2] to create a new collection of intercultural recordings designed to support palliative care patients and their caregivers. At the onset of this project, a commitment was made to not only create the musical recordings but also a pre-production and research process that would foster an equitable and meaningful intercultural collaboration. It is this process that will be explored in detail in this paper. The authors propose that this process could help to inspire further equitable and inclusive intercultural collaborative practices in both musical and non-musical settings such as health care as several aspects of this collaborative process may be useful for other initiatives that require cultural sensitivity and intercultural collaboration. 
 
 [1] Names have been redacted for the purposes of submission to the journal, names will be put back in for final published version.
 [2] Names have been redacted for the purposes of submission to the journal, names will be put back in for final published version.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.311
Threshold uncertainty score0.450

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.041
GPT teacher head0.414
Teacher spread0.373 · 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