“Remove Your Mask”: Character Psychology in Introspective Musical Theatre – Sondheim’s <i>Follies</i>, LaChiusa’s <i>The Wild Party</i>, and Stew’s <i>Passing Strange</i>
Bibliographic record
Abstract
ABSTRACT: While earlier musicals, which developed popular songs, tended to focus on romance, differing backgrounds of the two members of a romantic couple, and their acceptance of each other and into a community, introspective musicals, which Stephen Sondheim pioneered after rock ’n’ roll began to define popular music, often dramatize psychological layers by exploring the discrepancy between the persona a character constructs and the character’s true inner self. I examine the way introspective musicals construct a paradigm of psychological growth, which usually involves characters’ creating strong masks/personae to hide their authentic selves and then ultimately gaining the courage to remove those masks. By looking at the construction of personae and their eventual attempts to accept emotional vulnerability – in Stephen Sondheim’s Follies, Michael John LaChiusa’s The Wild Party, and Stew’s Passing Strange – I explicate the way smaller, post-Sondheim musicals have shifted toward dramatizing an isolated character’s emotional development.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.016 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".