Bibliographic record
Abstract
The racist discourse of Québécois nationalist Pierre Falardeau (quoted in Alioff 1994, 13) which others the Indigene nationalist as a target for violence is created and maintained, in part, through the circulation of representations that stereotype First Nations as intellectually challenged, blood-thirsty or Noble Savages, the fossilized remains of a culture that belongs to the historical past. For Ward Churchill, these types of literary and cinematic images constitute ‘fantasies of the master race’, the ironic title of his study examining the roles played by literature and cinema in the colonization of American Indians.1 In her introduction to Churchill’s book, M. Annette Jaimes characterizes such representations as ‘weapons of genocide’ (quoted in Churchill 1992, 1); they provide misinformation deforming human subjects with highly developed social, cultural, economic, agricultural and linguistic systems into non-human, primitive obstacles to colonization or settlement. The classical Hollywood western emplots genocide as a jingoistic and triumphalist narrative of conquest that gives birth to the white US nation. Although the narrative works to elide it, the film of contested ‘Indian’ nation is palpable inside the classical Hollywood western. The violence of Native Americans in classical Hollywood films, while it may be coded as a sign of savage bloodlust by the film-maker, signals an irruption of resistance to aggressive acts of invasion or settlement to the spectator who reads the screen oppositionally. Sympathetic depictions of the imperial violence waged against Amerindian nations come much later through the agency of a white character and camera eye in films such as Little Big Man (Arthur Pen 1970) and Dances With Wolves (Kevin Costner 1990).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.075 | 0.008 |
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".