The Money Shot: Postmodern Economies of Sex, Guns, and Language in Topdog/Underdog.”
Bibliographic record
Abstract
In “An Equation for Black People Onstage,” playwright Suzan-Lori Parks lays out the difficulty of writing plays about black people without falling into an essentializing “Black Aesthetic.” Theatre, she argues, is useful for black people because it “can ‘tell it like it is’; ‘tell it as it was’; ‘tell it as it could be’” (21); and, indeed, Parks's plays are continually exploring the limits and intersections of all three. “[T]he writing is rich,” she continues, “because we are not an impoverished people, but a wealthy people fallen on hard times” (21). When we consider this metaphor in light of Parks's well-known dramaturgical focus on black male characters, it becomes a highly charged one. In Topdog/Underdog, for example, Lincoln, a previously married and relatively prosperous hustler, has been left by his wife and is now working in a mall, dressing up as the historical Lincoln; his brother, Booth, has likewise been abandoned by his girlfriend, Grace, and is wholly dependent on Lincoln for money other than what he can make pawning stolen goods. Both characters are in crisis – economically and with respect to their masculinity – and Parks's notion of wealth is both a cause of and a metaphor for the crisis.
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
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Literary criticism of a play; abstract absent but the title is unambiguous.
The work analyzes literature and language rather than research itself.
Literary criticism of a play, not research practice or scholarly communication as objects of study.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 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".