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Record W2009804062 · doi:10.1177/002242940505300206

Effects of Excerpt Tempo and Duration on Musicians' Ratings of High-Level Piano Performances

2005· article· en· W2009804062 on OpenAlexaff
Joel Wapnick, Charlene Ryan, Louise Campbell, Patricia Deek, Renata Lemire, Alice-Ann Darrow

Bibliographic record

VenueJournal of Research in Music Education · 2005
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsMcGill UniversityCentre for Interdisciplinary Research in Music Media and Technology
Fundersnot available
KeywordsPianoPsychologyDuration (music)Test (biology)Consistency (knowledge bases)AudiologyPopulationDevelopmental psychologyDemographyMathematicsMedicineArtSociologyLiterature

Abstract

fetched live from OpenAlex

The purpose of this study was to determine how judgments of solo performances recorded at an international piano competition might be affected by excerpt duration (20 versus 60 seconds) and tempo (slow versus fast). Musicians rated performances on six test items. Results indicated that piano majors rated slow excerpts higher than they rated fast excerpts, and that they rated slow excerpts higher than nonpiano majors rated either slow or fast excerpts; undergraduates rated long excerpts the same as or slightly higher than they did short excerpts, but graduate students and faculty rated long excerpts markedly higher than short excerpts; and undergraduate piano majors rated performances lower than did undergraduate nonpiano majors, but graduate piano majors and faculty rated performances higher than did graduate/faculty nonpiano majors. Also, accuracy items correlated with each other more highly than they did with other items, and judge ratings were higher for accuracy items than they were for other items. Finally, judge consistency was shown to be related to excerpt duration, excerpt tempo, instrumental major, and level of education. Results generally show that ratings taken after 60 seconds differed from ratings taken after 20 seconds, and that ratings provided evidence that judges were able to distinguish between different test items. November 23, 2004 April 27, 2005.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.205
Threshold uncertainty score0.271

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.102
GPT teacher head0.396
Teacher spread0.294 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations24
Published2005
Admission routes1
Has abstractyes

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