MétaCan
Menu
Back to cohort
Record W4417442913 · doi:10.62410/n0bt1b66

Mieux comprendre le processus de co-création d’une chanson : la réflexivité au service d’un projet de recherche-création

2025· article· W4417442913 on OpenAlexaff
Sarah-Anne Arsenault

Bibliographic record

VenueMusiques, recherches interdisciplinaires : · 2025
Typearticle
Language
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsContext (archaeology)Sandbox (software development)Order (exchange)

Abstract

fetched live from OpenAlex

How are ideas intertwined during a co-creation process? What kind of relationship develops between the co-creators and their work? Why is co-creation sometimes so difficult, even in an atmosphere of trust and respect? While collaborative creation has been the subject of much research in education and psychology, it remains relatively unstudied in its own right, as a specific mode of creation. This article reports on a musicology project adopting a research-creation approach. The research component aims to better understand the co-creation process of a song through active participant observation (APO), while the creation component aims to produce a song that is meaningful to its co-creators. Through a hermeneutic and reflective approach, I demonstrate that considering my own journey within this project allowed me to better understand the complexity of the creative, collaborative, and interactional components of the co-creation process. My analyses, based on transcripts, a logbook, individual interviews, and cross-self-confrontation, also enabled me to reflect on the role of a person in a position of authority within a co-creation group: how can they intervene to "facilitate" the creative process while minimizing their influence on it? Indeed, I chose to collaborate with young people aged 15 to 17 with no prior songwriting experience, thus testing Vygotsky's (1981) concept of the zone of proximal development. In summary, my results show that resorting to a more traditional epistemological stance would not have allowed us to reveal certain intersubjective subtleties of the co-creation process, such as the surprising ambiguity of the link that unites the co-creators to their song.

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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.732
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.003
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 head0.212
GPT teacher head0.401
Teacher spread0.189 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueMusiques, recherches interdisciplinaires :Same topicDiverse Music Education InsightsFrench-language works237,207