Bibliographic record
Abstract
Guest Editor Patricia Shehan Campbell introduces this Special Issue of the Journal of Popular Music Education focusing on ‘Girls and Women in Popular Music Education’. Campbell briefly sets the scene, articulating something of the urgency of the need to pay more and long overdue attention to women in popular music – both in and for popular music education. Campbell introduces articles by each of the authors featured in this Special Issue, outlining the thrust and key points in each case. She introduces Claire Anderson’s article on spectaculars; Lloyd McArton’s paper on Toronto indie musicians; Clayton Dahm’s writing on Malian musician Oumou Sangaré; Kelsey Guo and Mari Shiobara’s piece about the enduring appeal of Teresa Teng; J. Michael Kohfeld’s article about LGBTQ+ representation in college music curricula; Carol Shansky’s article on well-known harmonica players; Ailbhe Kenny’s study of African migrant DJs in Ireland; and Juliana Cantarelli Vita’s paper about the Brazilian ensemble, Dita Curva.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.000 |
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 teacher head, 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".