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Record W1992996206 · doi:10.3138/md.53.3.332

I was a Teenaged Fabulist: The <i>dark play</i> of Adolescent Sexuality in U.S. Drama

2010· article· en· W1992996206 on OpenAlexvenueno aff
Brian Eugenio Herrera

Bibliographic record

VenueModern Drama · 2010
Typearticle
Languageen
FieldArts and Humanities
TopicTheatre and Performance Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDramaMiddlebrowPrideGossipHistoryArtMedia studiesSociologyLiteratureGender studiesPsychologySocial psychologyLawPolitical science

Abstract

fetched live from OpenAlex

The breakout hit of the 2007 Humana Festival, Carlos Murillo's dark play or stories for boys received wide notice for its provocative theatricalization of the “true” story of “one teenager's near-fatal internet attraction.” In subsequent professional productions in major U.S. cities including Los Angeles, Atlanta, Philadelphia, and Salt Lake City (as well as scores of university productions nationwide), Murillo's dark play has been routinely promoted as a tale of contemporary teen life, depicting dangers and deceptions peculiar to the Internet age. In this article, I argue that the significance of Murillo's dark play derives less from its contemporaneity than from its clarifying evocation of the longer history of staging sexually precocious adolescent characters within U.S. middlebrow drama since the early decades of the twentieth century. As I trace how such intimate dramas of gossip, rumour, and innuendo evoke the “dangerous games” played by adolescent characters in mid-century works by Lillian Hellman, Arthur Miller, and Robert Anderson, this article explicates how the “teen fabulist,” the kid who makes stuff up about herself or himself and others, emerges as a privileged device through which U.S. dramatists have sought to stage otherwise unstageable uncertainties about morality, hypocrisy and societal norms configuring “truth.”

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0080.007
Scholarly communication0.0050.002
Open science0.0000.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.021
GPT teacher head0.237
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations14
Published2010
Admission routes1
Has abstractyes

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