Bibliographic record
Abstract
THE PLAINSMAN (1937): CECIL B. DeMILLE'S GREATEST AUTHENTICITY LAPSE? Cecil B. Demille was a seminal founder of Hollywood whose films were frequently denigrated by critics for lacking historical verisimilitude. For example, Pauline Kael claimed that DeMille had "falsified history more than anybody else" (Reed 1971: 367). Others argued that he never let "historical fact stand in the way of a good yarn" (Hogg 1998: 39) and that "historical authenticity usually took second place to delirious spectacle" (Andrew 1989: 74). Indeed, most "film historians regard De Mille with disdain" (Bowers 1982: 689) and tended to turn away in embarrassment because "De Mille had pretensions of being a historian" (Thomas 1975: 266). Even Cecil's niece Agnes de Mille (1990: 185) diplomatically referred to his approach as "liberal." Dates, sequences, geography, and character bent to his needs." Likewise, James Card (1994: 215) claimed that: "DeMille was famous for using historical fact only...
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.012 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.008 | 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".