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Record W4413781462 · doi:10.29173/inton96

Reconsidering Metronomic Precision

2025· article· en· W4413781462 on OpenAlexaffvenue
Arlan Vriens

Bibliographic record

VenueIntonations · 2025
Typearticle
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

This paper explores the historical and contemporary implications of the metronome’s role in defining pulse and tempo in Western art music. Far from 18th-century conceptions of pulse anchored in the tempo giusto and described with reference to the musician’s literal heartbeat, the 21st-century performer is much more likely to consider the metronome as the source and arbiter of a “correct” pulse. The evolution of the metronome from its earliest mechanical iterations through to contemporary smartphone apps also maps neatly onto the increasing societal trust placed in the metronome as authority. This relocation of the source of pulse from internal (the performer) to external (the metronome) also brings psychological impacts, particularly with reference to music performance anxiety; the expectation of matching digitally precise timekeeping with a fallible human body is a contributor to anxiety and self-doubt among musicians. Using detailed pulse analyses of mid-20th-century electromechanical metronomes as case studies, this paper describes how the idiosyncratic pulse shifting and surging of these devices inadvertently gesture toward a reimagined role for the device. The author concludes by proposing the development of digital metronomes with a switchable “fallibility” mode, which might introduce varying degrees of pulse variability to the metronome, thereby granting musical artists the creative agency to follow or resist the device, much as they would a live musical partner. Such a development is also proposed as a step forward toward understanding constructive approaches to other nascent music practice aids such as increasingly precise tuners or apps which propose to objectively define “quality” tone.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.903
Threshold uncertainty score0.142

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.038
GPT teacher head0.274
Teacher spread0.236 · 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 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

Citations0
Published2025
Admission routes2
Has abstractyes

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