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Record W4405510688 · doi:10.1177/20592043241294161

Music Research “in the Wild” – Introducing the MusicLab Copenhagen Special Collection

2024· article· en· W4405510688 on OpenAlexaboutno aff
Simon Høffding, Niels Chr. Hansen, Alexander Refsum Jensenius

Bibliographic record

VenueMusic & Science · 2024
Typearticle
Languageen
FieldComputer Science
TopicMusic and Audio Processing
Canadian institutionsnot available
FundersNorges ForskningsrådNordForsk
KeywordsPsychology

Abstract

fetched live from OpenAlex

Some of the most intense human experiences unfold while performing and listening to music. For both performers and listeners, active musical experiences—sometimes called acts of musicking (Small, 1998)—regulate our emotions, guide our attention, and generate prosocial behavior. It is no surprise, then, that philosophy, musicology, sociology, biology, and psychology have been occupied with understanding how and why music mediates these intense experiences. Yet, it has been difficult to produce reliable scientific knowledge while, at the same time, preserving the liveness of music as it unfolds in concert venues. In response to this challenge, concert research is emerging as a research topic involving interdisciplinary investigations of music, interaction, consciousness, cognition, physiology, behavior, and technology within a concert venue (Tröndle, 2021; Wald-Fuhrmann et al., 2021). With recent rapid developments in wearable sensing devices, it is now possible to perform research “in the wild” with real audiences and musicians. In this way, we are gradually getting a better grasp of what it is about live music that makes it so enriching. By analyzing the experiences, behaviors, and interactions of both musicians and audiences, we can develop methods to understand the entire ecosystem of the concert experience, even if we do not arrive at exhaustive explanations. Several groups are now pursuing such investigations, for instance, McMaster's LIVElab in Canada, the Max Planck Institute for Empirical Aesthetics in Frankfurt, the Experimental Concert Research team in Berlin, and RITMO Centre for Interdisciplinary Studies in Rhythm, Time, and Motion at the University of Oslo (UiO). This special collection of Music & Science contains 111 articles. They thoroughly describe a particular instantiation of a research concert, namely the innovative and complex event MusicLab Copenhagen. This took place over 14 hours on October 26, 2021, in Copenhagen, Denmark. Working with The Danish String Quartet (DSQ), one of the world's best chamber ensembles, a research team from RITMO, complemented with researchers from several other European institutions, ran experiments and studied how mind and body are engaged during a concert. This was a unique opportunity to capture concurrent qualitative, behavioral, and physiological measurements in a concert hall, delicately balancing the scientific ideals of reliability and ecological validity.

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)0.005
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.071
Threshold uncertainty score0.236

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.003
Science and technology studies0.0020.005
Scholarly communication0.0090.007
Open science0.0020.008
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0710.038

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 head0.091
GPT teacher head0.338
Teacher spread0.247 · 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 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

Citations3
Published2024
Admission routes1
Has abstractyes

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