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Record W2312521491 · doi:10.1177/8755123314548041

A Dialogue of Necessity

2014· article· en· W2312521491 on OpenAlexaff
Shelley M. Griffin, Linda Ismailos

Bibliographic record

VenueUpdate Applications of Research in Music Education · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsBrock University
Fundersnot available
KeywordsNarrativeMusic educationPsychologyCompetence (human resources)PedagogyBachelorTeacher educationIdentity (music)Narrative inquiryPerceptionRelevance (law)Mathematics educationSocial psychologyAestheticsLinguistics

Abstract

fetched live from OpenAlex

Many teacher candidates (preservice teachers) in a Bachelor of Education degree cross the threshold into an elementary music methodology course with trepidation. Thus, teacher educators (music education professors) ought to explore the ways in which they can attend to students’ music experiences so as to increase teacher competence. This article explores three relevant areas of literature: fear of teaching music, relevance of informal music learning on influencing teacher identity, and influence of such experiences on teacher education programs. Building on this literature, the article concludes with highlighting a 2-year narrative inquiry exploring how the daily music experiences of teacher candidates’ inform their teaching practices. Through the use of visual narratives (body maps), oral and written narratives, and conversational interviews, 20 participants gave voice to their multilayered experiences that influenced their perceptions about music teaching. Findings deepen conceptualizations concerning the power of informal music learning in shaping teacher identity and practice.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.858
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
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 head0.103
GPT teacher head0.357
Teacher spread0.255 · 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 designTheoretical or conceptual
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

Citations9
Published2014
Admission routes1
Has abstractyes

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