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Record W2945341997 · doi:10.4324/9780203344262-20

Is music autonomous from language? A neuropsy chological appraisal

2004· book-chapter· en· W2945341997 on OpenAlexaboutno aff

Bibliographic record

VenuePsychology Press eBooks · 2004
Typebook-chapter
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceLinguisticsPsychologyPhilosophy

Abstract

fetched live from OpenAlex

Department of Organismic and Evolutionary Biology, Harvard University, USA Isabelle Peretz Département de Psychologie, Université de Montréal, Canada INTRODUCTION Music and language are universal among humans, and both employ richly structured auditory and motor patterns. Since music and language are the two primary acoustic communicative systems of our species, their similarities and differences as cognitive domains have long interested scholars. (e.g. Aiello, 1994; Albert, Sparks & Helm, 1973; Besson, Faïta, & Requin, 1994; Bernstein, 1976; Blacking, 1976; Clarke, 1989; Darwin, 1871; Handel, 1989; Judd, Gardner & Geschwind, 1983; Lerdahl & Jackendoff, 1983; Levman, 1992; Nettl, 1956; Rousseau, 1761; Selkirk, 1984; Sergent, 1993; Sloboda, 1985; Sundberg & Lindblom, 1976; Sundberg, Nord & Carlson 1991; Trehub & Trainor, 1993). These contributions highlight the diversity of fields which have addressed this issue, from philosophy to the social, psychological, and biological sciences.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.004
Scholarly communication0.0020.003
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.122
GPT teacher head0.359
Teacher spread0.237 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations46
Published2004
Admission routes1
Has abstractyes

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Same venuePsychology Press eBooksSame topicNeuroscience and Music PerceptionFrench-language works237,207