Bibliographic record
Abstract
The surprising thing about Tom Stoppard is that – for all his reputation as a “cutting edge” dramatist, dealing with highly contemporary issues, tackling immediately relevant themes – i n his whole d ramatic output there a re on ly four full-length stage plays actually set in the present. These are Night and Day and Jumpers and Hapgood, along with his ironically titled, semi-autobiographical The Real Thing and his very first play, Enter a Free Man – although Stoppard has dismissed this as an amalgam of other people’s plays. Eighteen of his remaining nineteen full-length plays are set wholly or at least partially in the past, qualifying him for the title “historical playwright,” a fact that makes him quite unusual among major twentieth-century British playwrights. There are, of course, others who have turned to historical subjects, among them Edward Bond and Caryl Churchill. Yet neither of these has set more than one in three of their dramas in the past, and Churchill, for example, moves away from the historical, with most of her history plays being clustered in her early career. Perhaps the only playwright who has anything approaching the same weight of historical drama in his total output is Peter Barnes, whose plays are set in eras so distant and different from our own that the effect is estranging.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.009 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 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".