Bibliographic record
Abstract
Although multitrack audio recordings are a critical component of nearly every recorded musical work, they have historically been difficult to acquire because of their commercially sensitive nature. However, one example of an emergent archive and collections, that allows researchers to peer into the record company vaults, is the EMI Music Canada Archive at the University of Calgary (UofC) in Canada. This archive holds demo tapes, song lyrics, concert planning documents, promotional material, cover art, correspondence between artists, management, producers and executives in addition to the multitrack tapes of the recordings. The following chapter draws upon materials gathered from the UofC Archives, (that of Canadian Rock band ‘Grapes of Wrath’ and their album These Days (1991) produced by British Record Producer John Leckie) and describes how researchers at the University of Victoria in British Columbia, Canada, Drexel University in Philadelphia, USA, and Leeds Beckett University in Leeds, UK, designed and delivered a mixing course to students using these materials. Students were asked to reflect on their own learning and experience throughout the project and these reflections helped to show that focusing on telling the story of the record, and using the additional archival materials to do so, did more than just improve students’ technical mixing skills. Instead, it helped the students to develop a wider appreciation of the ways in which their creative decisions might be received by the relevant stakeholders such as the band, the producer, etc. and, importantly, helped them better understand their role as a mix engineer within the production process .
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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.096 | 0.051 |
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".