Review: Understanding the Women of Mozart's Operas by Kristi Brown-Montesano
Bibliographic record
Abstract
Book Review| December 01 2008 Review: Understanding the Women of Mozart's Operas by Kristi Brown-Montesano Understanding the Women of Mozart's Operas, by Kristi Brown-Montesano. Berkeley, Los Angeles, and London: University of California Press, 2007. xxv, 316 pp. Edmund J. Goehring Edmund J. Goehring EDMUND J. GOEHRING is Assistant Professor of Music History at the University of Western Ontario. He received his PhD from Columbia University and awards and fellowships from the AMS, the NEH, and the Social Science and Humanities Research Council in Canada. His articles have appeared in The Cambridge Opera Journal, Eighteenth-Century Music, and The Publications of the Modern Language Association. Search for other works by this author on: This Site PubMed Google Scholar Journal of the American Musicological Society (2008) 61 (3): 609–615. https://doi.org/10.1525/jm.2008.61.3.609 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Twitter LinkedIn Tools Icon Tools Get Permissions Cite Icon Cite Search Site Citation Edmund J. Goehring; Review: Understanding the Women of Mozart's Operas by Kristi Brown-Montesano. Journal of the American Musicological Society 1 December 2008; 61 (3): 609–615. doi: https://doi.org/10.1525/jm.2008.61.3.609 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentJournal of the American Musicological Society Search This content is only available via PDF. © 2008 by the American Musicological Society. All rights reserved.2008 Article PDF first page preview Close Modal You do not currently have access to this content.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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".