Bibliographic record
Abstract
When The Winslow Boy, with screenplay and direction by David Mamet, premiered in 1999, critics scrambled to account for Mamet's uncharacteristic choice of subject and setting. Variously termed a costume piece (Null), Mer-chant-Ivory fare (Macnab), and an Edwardian drama (James 22), the film was consistently noted to be far removed from Mamet's apparently typical "hide-and-seek scenarios featuring characters who fire off tough-guy, staccato dialogue at machine-gun velocity" (Sipe) or "lowlifes and con men, gamblers and thieves" (Ebert). Although Mamet himself acknowledges that the film marks a "departure," he qualifies that observation with the statement that he is departing only "from some of [his] other work" (qtd. in Graham 231). Indeed, while critics in one breath note the vast difference between the subject of The Winslow Boy and that of Mamet's films and plays, they tend to search for and ultimately assert a thematic or linguistic emphasis consistent with that of Mamet's work. That similarity has been seen to lie in the film's apparent interest in "whether an offscreen crime really took place" (Ebert), in its use of "trademark" Mamettian ellipses and overlapping dialogue (Kelleher), and in its dissection of assumed social and domestic values (McIntire-Strasburg).
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.017 | 0.014 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".