Bibliographic record
Abstract
Conrad's dramatic adaptation of his well-known novel The Secret Agent (1907) was first performed in 1922, that watershed year for literary modernism, and it is striking in its attempts to translate the narrative's innovative theatricality into the play's literal theatre. That this translation is not quite successful is telling, for sure, about Conrad 's limitations as a dramatist, but it is rather more telling about the incompatibility between modernist conceptions of culture, which are integral to Conrad's story, and a (mostly) realist dramatic form, with which Conrad tries to replicate the novel's work. Conrad's modernist sensibility is most apparent in the play's few moments of address to its audience, in which Winnie Verlac, the secret agent's wife, looks out from the stage to affirm her spectators as participants and interlocutors. In these episodes, Winnie is reminding her audience that it knows what she knows: that it knows and she knows that her life incorporates habitual scripts and that she is conforming, against her wishes, to a melodramatic plot. From her wry comment in the first act, "Yes, I am lucky" (referring to her marriage, in which she knows she is not lucky), to her assertion late in the play, "No! That must never be!" (referring to prison or hanging), Winnie asks the audience to notice that the gestures and expectations of conventional fiction arc internal to the culture that Conrad's fiction represents.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.023 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".