Review of Dylan Robinson, <i>Hungry Listening: Resonant Theory for Indigenous Sound Studies</i> (University of Minnesota Press, 2020)
Bibliographic record
Abstract
Recent activities in the Society for Music Theory suggest that its members are ready to call out the discipline's faults and are hungry for change.Events such as the founding of Project Spectrum in 2018 as a graduate-student-led coalition for reform across the music disciplines (Project Spectrum 2020), the 2019 SMT annual meeting's keynote addresses exposing the discipline's faults in numerous ways (West Marvin et al. 2019; Ewell 2020), and the scandal surrounding the publication of volume 12 of the Journal of Schenkerian Studies (2019) may have inspired music theorists to consider the many problematic aspects of music theory and analysis as currently practiced in institutions drawing from the Western European music conservatory model (A as 2019; Walker 2020).Some may be reflecting on the ways these considerations recall and return to previous discussions on related topics: among them, gender (Parsons and Ravenscroft 2017; Maus 1993), race and ethnicity (Ewell 2009; Hisama 2016, 2018a, 2018b), sexuality (Bre , Wood, and Thomas 2006; Maus 2020) and general curricular reform (Campbell et al. 2014).
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 0.007 |
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".