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Record W2950575417

An Historical Study of the First Year of the Canadian Association of Music Therapists

2019· dissertation· en· W2950575417 on OpenAlexaboutno aff
Kruger Daniel

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2019
Typedissertation
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsnot available
Fundersnot available
KeywordsNarrativeIdentity (music)Music therapyQualitative researchPsychologyMedicineMedical educationSociologyPsychotherapistSocial scienceArtAestheticsLiterature
DOInot available

Abstract

fetched live from OpenAlex

This study presents a historical narrative of the inaugural year (1974/75) of the Canadian Association of Music Therapists (CAMT). The purpose of the study was to examine music therapists’ lived experiences of the first year of the CAMT concomitantly with primary source documents published between the first two CAMT conferences (August 3, 1974 and May 2, 1975, respectively). The primary research question was: What are the experiences of music therapists who were involved in the CAMT during its inaugural year? The secondary research question was: How do primary source historical documents from the first year of the CAMT relate to the experiences of the participants? I combined phenomenological and historical methodologies in this qualitative interview study. I interviewed three Canadian music therapists who were active during 1974/75. The experiences they shared in their interviews were related to primary source historical documents the researcher obtained from the CAMT historical archives. Three primary themes emerged from the data analysis: “developing identity,” “defining music therapy/music therapist,” and “emerging alternative profession.” This study offers information about significant conflicts, issues, and developments in the early CAMT that was previously missing from the historical literature on Canadian music therapy.

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)0.006
metaresearch head score (Gemma)0.012
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: Empirical
Teacher disagreement score0.881
Threshold uncertainty score0.863

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0060.010
Science and technology studies0.0540.018
Scholarly communication0.0120.003
Open science0.0030.006
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0060.001

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 head0.040
GPT teacher head0.314
Teacher spread0.275 · 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
Published2019
Admission routes1
Has abstractyes

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