Bibliographic record
Abstract
The genius that marks Shakespeare's work is apparent not just in such large matters as plotting, characterization, and language; it is also to be found in the smaller details — such as exits. In Shakespeare's use of them, exits do not merely get characters off stage, but are a means of dramatizing and encapsulating the chief concerns of a play. While I would not insist that he was the only playwright to capitalize on exits as he does, I believe one would be hard put to find the same subtle and ingenious use of them in the plays of his contemporaries. Even in Shakespeare's work, of course, not every exit can be related meaningfully to what the play is about: some are merely necessary, and are managed as simply as possible; but more often than not a character's departure from the stage is both itself a visual and verbal event which is directly pertinent to the issues at stake as well as one in a series of exits that highlights the tragic, comic, or tragicomic process of a play. And on the stage for which Shakespeare wrote, which had minimal scenery and no variable lighting, the potential significance of exits was doubtless more apparent, and perhaps more real, than it is today for both the playwright and his audience.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.045 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".