Bibliographic record
Abstract
No area of Samuel Beckett's work has received less attention than his television drama, and the least studied of his six teleplays is Nacht und Träume . Although the premiere broadcast of Nacht und Träume attracted an audience of two million, the teleplay is rarely seen today except at Beckett festivals and modem drama conferences. Nor should one expect a "Beckett revival" on commercial television any time soon. Envisioning such a revival, Eckart Voigts- Virchow cleverly hypothesizes that the ratings would "rocket through the floor." One expects mainstream resistance to works like Nacht und Träume, which challenge television's formulaic conventions and passive viewing habits. What is more puzzling, however, is the slight attention paid this teleplay within Beckett circles. Even among the author's most dependable champions, Nacht und Träume has been dismissed too easily. Martin Esslin, for instance, concedes that it offers an "extremely powerful" image, but concludes that it is, "for my taste, somewhat too sentimental." Beryl and John Fletcher accuse Nacht und Träume of being less visually interesting than Beckett's other teleplays, and they voice doubt as to "whether this script makes for a successful or effective use of the medium." Even James Knowlson, who praises the teleplay unconditionally, has a difficult time locating its specific appeal.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.010 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".