Bibliographic record
Abstract
How did women concert artistes assess other women performers? This chapter focuses on Clara Schumann’s private writings about piano virtuosas between the 1830s and 1842. Schumann’s commentaries offer many fresh insights. She identifies an unexpectedly large number of women concert pianists active in German-speaking Europe and names those who helped younger female colleagues; she also shows that most virtuosas composed, and performed their works in public. Perhaps most strikingly, Schumann exposes a professional environment fraught with intrasexual pressures. Often invited to play at the same soirées, and compared to each other by hosts, promoters, and reviewers, women artistes regularly navigated gendered workplaces. These circumstances explain why Schumann portrayed most virtuosas as challengers. This chapter argues that the intrasexual negativity and internalized sexism that coloured Schumann’s writings reflect the gender imbalance in her working environment, as women tend to compete against each other when pursuing career advancement in male-dominated professions.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.020 | 0.023 |
| Scholarly communication | 0.018 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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".