"Looka Me, I'm the Force o'Wisdom and Progress!": Un-Crowning the Classic Text Through Carnivalesque Dramaturgy
Bibliographic record
Abstract
Adaptation scholarship often laments the anti-adaptation biases that infuse what they call “fidelity discourse” (criticism based on the assumption that adaptations can and should be assessed only on the basis of their fidelity to the source). However, few scholars have acknowledged that since adaptors themselves are well-aware of fidelity discourse, they must somehow negotiate it; this can involve pre-empting, evading, or challenging it. This essay explores how playwright Michael O’Brien negotiates and even exploits commonplace prejudices about adaptation—especially comic adaptations—in Mad Boy Chronicle, his 1995 travesty of Hamlet. The essay examines both the carnivalesque dramaturgy of Mad Boy Chronicle, to illustrate how its ostensibly dumb comedy is really in pursuit of serious knowledge, and O’Brien’s paratextual strategies for guiding the audience’s reception of the play. While the play itself presents the generic conventions of a “stoopid” parody, O’Brien takes pains to frame it in program notes, interviews, prefaces, and other publicity material, not as a comic desecration of a masterpiece, but as an earnest attempt to resurrect the original source of that so-called masterpiece. These framing tactics serve to destabilize the assumed superiority of the “original” by revealing that Hamlet itself is only an adaptation. Thus, while the adaptation relies on and confirms the prestige of the canonical source, it also forces us to reconsider it.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.034 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 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".