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Record W7064484803

Carareretetatakakekerers

2021· other· en· W7064484803 on OpenAlexaboutno aff

Bibliographic record

VenueRADAR (Glasgow School of Art) · 2021
Typeother
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsWork (physics)Point (geometry)GloomStaringFrame (networking)Noise (video)
DOInot available

Abstract

fetched live from OpenAlex

80-minute score and sound design for Normal Condition's contemporary dance work 'Carareretetatakakekerers', choreographed by Nicola Conibere. Premiere - 14 October 2021, Lilian Baylis Studio, Sadler's Wells, London. This electroacoustic score was composed for Carareretetatakakekerers, a choreographic work by Nicola Conibere, premiered by Normal Conditions at Sadler’s Wells in 2021. The research underpinning the composition explores how spatial and localised audio can reinforce the spatial distribution and movement of dancers on stage. Drawing on Henry Brant’s concept of Spatial Music (Brant, 1953) and John Cage’s principle of the co-existence of dissimilars (Cage, 1957), the score juxtaposes and disperses heterogeneous sonic materials across a multichannel speaker array. In line with Pierre Boulez’s notion of static and mobile distribution of sound (Boulez, 1963), and building on Denis Smalley’s writing on spatial articulation and spatiomorphology (Smalley, 1991; 1997), the work employs fixed sonic placements to denote architectonic zones within the performance space (Harrison, 1999), while mobile distribution of sound is used to support and accentuate the dancers’ movement across and between these zones. In doing so, the score does more than accompany the choreography, but participates in shaping a spatial dialogue — mirroring, shadowing, and at times anticipating movement. As such, spatialisation of audio is treated as a compositional parameter in its own right, contributing structurally and expressively to the work. As an electronic composition, the work operates within virtual space—more specifically, through spatial illusions that do not rely on simulating real-world acoustics. Smalley’s concept of spatiomorphology (1997) provides a framework for articulating how spatial change functions musically in the piece. Several of his spatial variants are directly explored. Internal and external space are invoked through contrasting acoustics that suggest enclosure versus openness; image definition is shaped by the clarity or diffusion of sonic gestures across the multichannel array; spatial texture is deployed to create layered distributions of voice and sound objects in time; and contiguous space is realised through mobile sonic gestures that trace, follow, and extend the dancers’ trajectories. These spatial behaviours are composed and realised as integral expressive elements, contributing to the relational and emotional tone of the choreography. The score also explores a range of psychoacoustic phenomena, including auditory illusions and phantom words (Deutsch, 2019). Pre-recorded spoken text, narrated by the dancers, are looped, layered, and phased across the speaker array. Through repetition and spatial displacement, these vocal fragments create auditory illusions in which phantom words appear to emerge internally—despite not being acoustically present. These effects are shaped by the listener’s linguistic background, cultural framing, and psychological filtering. As Deutsch observes, what is heard varies between individuals, invoking subjectivity as a compositional agent. These illusions operate, in part, as an allegory of brain fog (Abbasi, 2024)—a widely reported cognitive symptom of COVID-19—and also of mental slippage, where one cannot precisely identify the moment at which rhythm, sense, or orientation begins to shift. As loops gradually change, their rhythm morphs subtly, reflecting the instability and interdependence of the choreographic relationships on stage. Developed during the COVID-19 pandemic, the work also reflects adaptive and remote creative processes, shaped by masked rehearsals, spatial distancing, and shared constraints. Supported by Arts Council England, the project contributes to research in spatial audio, embodied listening, psychoacoustics, and interdisciplinary performance. References • Abbasi, J. (2024) ‘“Brain fog” from long COVID affects millions—what have researchers learned so far?’, BMJ, 385, q897. • Boulez, P. (1963) Boulez on Music Today. London: Faber & Faber. • Brant, H. (1953) Space as an Essential Aspect of Musical Composition and Performance. Canadian Music Council. • Cage, J. (1957) ‘Experimental Music’. Address given to the convention of Music Teachers National Association, Chicago, 1957. Reprinted in Silence: Lectures and Writings (1961). Middletown, CT: Wesleyan University Press. • Deutsch, D. (2019) Musical Illusions and Phantom Words: How Music and Speech Unlock Mysteries of the Brain. Oxford: Oxford University Press. • Harrison, J. (1999) ‘Sound, Space, Sculpture: Some Thoughts on the “What”, “How” and “Why” of Sound Diffusion’, Organised Sound, 3(2), pp. 117–127. • Smalley, D. (1991) ‘Spatial Experience in Electro-Acoustic Music’, Proceedings of the International Computer Music Conference (ICMC), Montreal: ICMA, pp. 458–461. • Smalley, D. (1997) ‘Spectromorphology: Explaining Sound-Shapes’, Organised Sound, 2(2), pp. 107–126.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.947
Threshold uncertainty score0.177

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0530.007

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 head0.009
GPT teacher head0.251
Teacher spread0.242 · 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.

Study designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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