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Record W2061889862 · doi:10.1177/0255761410396966

Minding the music: Neuroscience, video recording, and the pianist

2011· article· en· W2061889862 on OpenAlexaffabout
Milton Schlosser

Bibliographic record

VenueInternational Journal of Music Education · 2011
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSadnessPsychologyAffect (linguistics)PerceptionFeelingPianoAffective neuroscienceMusic educationMoodCognitive psychologySocial psychologyCommunicationNeuroscienceAngerCognitionPedagogy

Abstract

fetched live from OpenAlex

Research in music education asserts that video review by performers facilitates self-directed learning and transforms performing. Yet, certain videos may be traumatic for musicians to view; those who perceive themselves as failing or experience performance-related failures are prone to feelings of distress and sadness that can negatively affect their music-making and well-being. In this study, the reactions of nine Canadian undergraduate pianists to reviewing themselves regularly on video are examined. The study was designed in two parts: first of all, to track the effects of watching self-referent videos of piano lessons and other performances; second, to highlight student responses to a Recital Review Protocol (RRP). The RRP was designed with instructors and students in mind, incorporating neuroscience strategies to reverse blood flow patterns in areas of the brain responsible for negative mood induction. The results from the first part of the study point to how regular video analysis is able to shift initial negative perceptions and transform practicing and performing. The findings from the second part indicate that more attention needs to be paid to students by instructors immediately after performances.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.568
Threshold uncertainty score0.246

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.083
GPT teacher head0.315
Teacher spread0.231 · 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

Citations6
Published2011
Admission routes2
Has abstractyes

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