MétaCan
Menu
Back to cohort
Record W7036745055

Collaboration for musical learning

2025· article· en· W7036745055 on OpenAlex

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

VenueEdge Hill University Research Information Repository (Edge Hill University) · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMediterranean and Iberian flora and fauna
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsSituatedScope (computer science)Context (archaeology)MusicalSituated learningMusic education
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this chapter is to enhance understanding and knowledge of the various possibilities and opportunities that collaboration can bring into secondary school music education. The chapter positions collaboration as a way of enhancing experience, learning and teaching for all involved. The benefits and challenges of collaboration are raised, situated within the wider context of music education policy and the complexities of individual teacher background, values and identity. Examples are provided of with whom a secondary school music teacher might collaborate , including collaborations within a teacher’s school, with feeder primary schools, instrumental teachers, musicians and higher education institutions. The reader is encouraged to thoughtfully consider the potential and scope of collaborations within their own context, and to take the first steps in the collaborative planning process. Models and theories are offered to frame the concept of collaboration, and conditions that can be put into place for collaborations to thrive are suggested.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.481
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
Bibliometrics0.0000.002
Science and technology studies0.0020.000
Scholarly communication0.0000.002
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 head0.028
GPT teacher head0.241
Teacher spread0.213 · 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