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Record W2120295438 · doi:10.1525/mp.2011.28.5.461

Probing the Minor Tonal Hierarchy

2011· article· en· W2120295438 on OpenAlexaff
Dominique T. Vuvan, Jon B. Prince, Mark A. Schmuckler

Bibliographic record

VenueMusic Perception An Interdisciplinary Journal · 2011
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsTonalityMelodyMajor and minorContext (archaeology)HierarchyMinor (academic)PsychologyPerceptionTone (literature)Speech recognitionComputer scienceMusicalLinguisticsArtHumanitiesAcousticsHistoryPhysicsVisual artsPhilosophy

Abstract

fetched live from OpenAlex

one facet of tonality perception that has been fairly understudied in the years since Krumhansl and colleagues' groundbreaking work on tonality (Krumhansl & Kessler, 1982; Krumhansl & Shepard, 1979) is the music theoretical notion that the minor scale can have one of three distinct forms: natural, harmonic, or melodic. The experiment reported here fills this gap by testing if listeners form distinct mental representations of the minor tonal hierarchy based on the three forms of the minor scale. Listeners heard a musical context (a scale or a sequence of chords) consisting of one of the three minor types (natural, harmonic, or melodic) and rated a probe tone according to how well it belonged with the preceding context. Listeners' probe tone ratings corresponded well to the minor type that had been heard in the preceding context, regardless of whether the context was scalar or chordal. These data expand psychological research on the perception of tonality, and provide a convenient reference point for researchers investigating the mental representation of Western musical structure.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.116
GPT teacher head0.334
Teacher spread0.217 · 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 designObservational
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

Citations34
Published2011
Admission routes1
Has abstractyes

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