Music from the Margins: An Autoethnographic Study of the Development of a Jazz Composer’s Voice
Bibliographic record
Abstract
This is a multi-modal, authoethnographic study which examines the development of my voice as a composer. It consists of a folio of music scores, two CD recordings, and an exegesis. The principal question of how my musical identity has been shaped by my experiences as a jazz practitioner has been examined through composing music, personal writing and reflection, and an examination of relevant literature. The compositions reveal the main influences in my musical identity - jazz, western art music and Latin music, as well as their connection to the places which have inspired their creation. They range from an art song cycle to Afro-Cuban dance music, reflecting the hybrid nature of my practice. The exegesis makes use of contemporary feminist musicology and cultural studies to examine the nature of my experiences as an Anglo-Canadian/Australian woman pianist trying to find her place in strongly male-identified Latin and jazz music communities. It addresses the historical eclipsing of the role of women in jazz, and examines the negotiation of gender dynamics in the job market and on the band stand in the various communities where I have lived and worked. Both the music and the narrative seek to add a unique voice to the ever-evolving and diversifying story of jazz in the 21st-century.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.012 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".