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Record W2948654607 · doi:10.36510/learnland.v12i1.994

Learners’ Identity Through Soundscape Composition: Extending the Pedagogies of Loris Malaguzzi With Music Pedagogy

2019· article· en· W2948654607 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.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueLEARNing Landscapes · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicArt Education and Development
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsSoundscapeIdentity (music)Active listeningMeaning (existential)Composition (language)NegationFocus (optics)Value (mathematics)Meaning-makingAestheticsSociologyPsychologyLinguisticsSound (geography)CommunicationArtAcousticsComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

It is astonishing to observe, listen, and co-learn with children as they engage with music to expand beyond the possible with their meaning-making abilities—immersing themselves in a hundred languages of music inspired by Loris Malaguzzi. In the current study, I examine how children in a split Grade 1/2 class explore and represent the sounds associated with city landmarks through soundscape composition. In particular, I focus on how students partake in the negation of identity. As a result of that, I have come to discover that by listening to children’s soundscapes we may be able to feel something new about particular landmarks, contemplate its value to citizens, and learn more about the meaning making of children.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.674
Threshold uncertainty score0.993

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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.000

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 head0.033
GPT teacher head0.281
Teacher spread0.249 · 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