Bibliographic record
Abstract
A Future In the Past is a research project engaging with the application of methods from Historically Informed Performance and Media Archeology towards problems found in the practice of Live Electronic music. In doing so the project sought to expose lost discourses in the medium as viewed from the performer’s perspective. Three pieces by composer Udo Kasemets were chosen as case studies. All compositions were originally written and performed prior to the 1990’s boom in digital processing. Each case study explores themes related to Liveness, Audience Interaction, and Hyper Instruments. In developing the historical context for each work several strategies were undertaken. Kasemets’ archives were reviewed at the University of Toronto, performers of the original pieces were interviewed, and investigations into period specific instruments were conducted. Additionally, Kasemets’ own published writings were used to reference his aesthetic ambitions as well as for comparison with his contemporaries. Rehearsals were carried out with The Estonian Electronic Music Ensemble, where the historical data and performer experiences were combined to create an individual interpretation for each composition. These interpretations were then presented to an audience and alongside contemporary issues currently debated in Live Electronics keywords: Live-electronics, historically informed performance, media archeology
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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.016 |
| Scholarly communication | 0.016 | 0.019 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.022 | 0.005 |
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".