Bibliographic record
Abstract
This dissertation is a study of select historical and contemporary vocalists who perform experimental jazz singing. I examine both their vocal techniques and the politics of their performance. Exceedingly little research addresses experimental vocal techniques in music that is mapped by scholars, audiences, and/or practitioners as jazz in any of its many guises. Yet from Abbey Lincoln screaming on We Insist! (1960), to Jay Clayton ululating on Sound Songs (1986), and present-day musicians such as Fay Victor, DB Boyko, and Christine Duncan, singers have been contributing to practices that they and their audiences view as related to jazz, while also, in some cases, pushing the boundaries of what jazz “is” by stretching beyond aesthetic and technical conventions that dominate(d) the jazz scenes in which they were involved. I engage with the music of artists such as these, those whose voices and musical contributions continue to be largely overlooked by scholars, audiences, and pedagogues. My close analysis of the sounds, techniques, and contexts for these performers’ innovations and interventions is framed by a critique of value structures that have rendered them all but inaudible except in certain spaces. As such, this dissertation has the potential to help readers expand their sound palette and query some of the assumptions underpinning their perspectives on music, especially jazz, in the first place. This work begins with a foundational chapter, which explores the lives and innovations of three Black American women all born in the 1930’s, who were central to the development of this music: Abbey Lincoln, Jeanne Lee, and June Tyson. In the following chapter, I move on to examine the career of vocalist Jay Clayton, who was crucial to the development of the Loft Scene in New York City in the 60s and 70s. Next, I examine the 2006 record Idiolalla by contemporary Canadian vocalists Christine Duncan and DB Boyko and percussionist Jean Martin. This chapter examines fears of vocal damage in this setting as well as recuperation techniques. Finally, this work ends with a compendium of 107 extended vocal techniques found throughout my research. This compendium includes descriptions as well as recordings of each technique.
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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.027 | 0.045 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".