Bibliographic record
Abstract
THE CINEMATIC "ARAB": FROM THE LONG SHIPS TO HIDALGO IMAGES of "Arabs" have been perennial staples of both Hollywood feature films and US television. The degree to which these are stereotypical has been examined in studies by several critics. In spite of their admonitions, however, they remain fixtures of America's dream factory. The recent film Hidalgo reveals the reproduction of these tried and not so true representations, but also seeks to address some of the criticisms and to make redress for transgressions visited upon the two principal groups depicted within it, "Arabs" and Native American Indians. In the course of doing so, it takes on North American "racial" formation, historical relations between the New and Old Worlds and British imperialism. Finally, Hidalgo is a curiously complex tricolour tapestry of racial binaries, the antinomies of "White" vs "Red," "Black" vs "White," "White" vs "Arab" and "Red" vs "Arab." If it...
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 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".