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Record W3007551847 · doi:10.1525/mp.2020.37.3.185

Cross-Cultural Work in Music Cognition

2020· article· en· W3007551847 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

VenueMusic Perception An Interdisciplinary Journal · 2020
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsUniversity of TorontoMcMaster UniversityUniversité de Montréal
FundersJapan Society for the Promotion of ScienceArts and Humanities Research CouncilHarvard Data Science Initiative, Harvard UniversityEuropean CommissionVlaamse regeringFonds Wetenschappelijk OnderzoekNational Institutes of HealthKeio UniversityNational Science Foundation
KeywordsTerminologyField (mathematics)PsychologyDisciplinePosition paperWork (physics)CognitionSociologyEngineering ethicsCognitive scienceSocial scienceComputer scienceEngineeringLinguistics

Abstract

fetched live from OpenAlex

psychology of music require cross-cultural approaches, yet the vast majority of work in the field to date has been conducted with Western participants and Western music. For cross-cultural research to thrive, it will require collaboration between people from different disciplinary backgrounds, as well as strategies for overcoming differences in assumptions, methods, and terminology. This position paper surveys the current state of the field and offers a number of concrete recommendations focused on issues involving ethics, empirical methods, and definitions of "music" and "culture."

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.957
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.003
Open science0.0010.000
Research integrity0.0000.001
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 head0.111
GPT teacher head0.376
Teacher spread0.265 · 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