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Record W2058797683 · doi:10.2979/pme.2010.18.2.111

The Shiver-Shimmer Factor: Musical Spirituality, Emotion, and Education

2010· article· en· W2058797683 on OpenAlexaff
Bogdan

Bibliographic record

VenuePhilosophy of Music Education Review · 2010
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMusicalFeelingPsychologySpiritualityActive listeningMusic psychologyAestheticsMusic and emotionDialecticTransformational leadershipSoulMusic educationPsychoanalysisSocial psychologyEpistemologyMusicLiteraturePhilosophyArtPedagogyCommunication

Abstract

fetched live from OpenAlex

This article offers one approach to exploring the question of in what sense music educators can speak of music and its moving power as spiritual by inquiring into what might count as a “musical spiritual experience” in emotional terms. The essay’s analytic framework employs the distinction between two related concepts which I call the “shiver” and the “shimmer” factors. The shiver factor is the physiological phenomenon of the “fingers-up-and-down-the-spine” feeling often experienced when listening to or performing a musical work. Employing an example from popular culture, this section of the essay evaluates “critical thinking” as a pedagogical tool for unpacking various mediarelated elements used to precipitate particular kinds of effects in respondents. The shimmer factor draws upon a combination of Csikszenthmihalyi’s “flow” and the Jungian conception of “soul-making” as a way of distinguishing a genuinely transcendent, transformational musical experience from a sensate, surface aesthetic encounter.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.009
Scholarly communication0.0040.003
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.080
GPT teacher head0.300
Teacher spread0.220 · 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

Citations22
Published2010
Admission routes1
Has abstractyes

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