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Record W4405392181 · doi:10.70121/001c.127453

Memory Retention in Classical Music: Exploring Strategies Through Examining Physiology, Repetition, and Participant Anecdotes

2024· article· en· W4405392181 on OpenAlexaff
Qingyun Liu

Bibliographic record

VenueScholarly review . · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsRepetition (rhetorical device)Classical musicPsychologyCognitive psychologyCognitive scienceCommunicationVisual artsArtLinguisticsMusicalPhilosophy

Abstract

fetched live from OpenAlex

This study will explore memory and the effects of repetition in the context of classical music performance. Specifically, the study will review the role repetition has in memory related functions such as retaining and recalling information in the context of classical music performance. This is done through drawing responses from the participants of a survey and through a literary review of relevant materials. Through the participants’ responses and studies related to memory retrieval in general and in music performance, it is evident that repetition can be highly beneficial for memory retainment and performance anxiety. This is crucial in understanding the role of repetition in memory and can lead to better results in music education and therapy. The study integrates both qualitative and quantitative findings to demonstrate the effectiveness of repetition-based practicing on memory in a musical context. By addressing both the physiological and psychological aspects of classical music performance, this study aims to provide insights into effective practice strategies in minimizing performance anxiety and its associated health risks.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.911
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.005
Open science0.0000.000
Research integrity0.0000.000
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 head0.412
GPT teacher head0.327
Teacher spread0.085 · 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.

Study designNot applicable
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

Citations0
Published2024
Admission routes1
Has abstractyes

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