Nightports at Hull Minster: Transporting a Site-Specific Musical Work Across Physical and Virtual Spaces
Bibliographic record
Abstract
'Nightports at Hull Minster' is a musical project that harnesses spatialisation techniques to present music composed of the sounds of Hull Minster, UK, in both the location itself and alternative performance spaces, whilst still expressing the spatiality of the location. The root of the project is a live electronic music performance by Nightports (The Leaf Label), using only sounds recorded in the Minster itself, spatialised in real-time by another performer across a 25-loudspeaker array in situ. Three variant performance approaches are detailed that allow this original principle of spatialisation to endure in contrasting locations: a physical acousmonium in-situ; a hybrid acousmonium and virtualmonium; and headphone-targeted virtualisations for radio. The compositional and performance processes, influenced by architectural and acoustic considerations, necessitated the development of a scalable and adaptable spatialisation system by the Hull Electroacoustic Research Organisation (HEARO). Alongside the technical implementations, this paper details performance observations including the interplay between spatial dynamics, audience interaction, and sonic immersion , while also offering insights into potential refinements and advancements in the spatialisation methods.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".