Bibliographic record
Abstract
The 1990s was Richard Attenborough's most prolific decade, directing four films with varying success. Despite all his efforts, Attenborough was unable to recapture the same degree of success he had enjoyed with Gandhi. One significant reason could be the change from the serious socio-political themes that had dominated Attenborough's productions, to one focusing on the people whose artistic talents held a particular personal interest for him, and, perhaps, less so for others. Of the four films two explore lives related to acting: Chaplin and Grey Owl. Chaplin focuses on the comic silent screen star, actor and director, Charles Chaplin. Grey Owl recounts the 'pseudo' life 'acted' by Archibald Belaney, an Englishman who masqueraded as a half-bred Native American Indian in Canada. The contradictions between the public and perceived identities which Grey Owl explored were also a significant factor in the film's lack of appeal to both critics and audiences.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.019 |
| Scholarly communication | 0.020 | 0.013 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.024 | 0.004 |
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".