The Intercultural Complexities of <i>Shoot The Indian:</i> An Interview with Archer Pechawis
Bibliographic record
Abstract
Shoot the Indian is a performance geared specifically to a mixed (read “non-Native”) audience. Presented during the Magnetic North Festival HIVE event, Shoot the Indian is an audience participation piece, where attendees have the opportunity to shoot a real Indian (Pechawis) with a paintball gun for five dollars. Riffing on the circus freak, vaudeville and old “Wild West” shows, this piece is a commentary on violence against Native people – a clown show, in other words. Pechawis stands in front of a 30-foot wide video projection wearing a beautiful Tsimshian mask (carved by Simon Reece) and a white painter suit. The mask serves a dual purpose: a challenge to the audience (will they shoot such a powerful cultural symbol?) and protection for Pechawis, as he has reinforced the mask with fiberglass. The video footage comes from old westerns edited down to the salient bits, namely Indians attacking whites. Pechawis includes a few sections of cowboys and cavalry playing in reverse. Shoot the Indian is available as a touring performance. Go to the web site to view the video footage of Shoot The Indian, HIVE, Vancouver BC, 2008 (adapted from “Shoot the Indian”).
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.032 | 0.031 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".