Turbans, Veils, and Villainy on Television: Stargate SG1 and Merlin
Bibliographic record
Abstract
In this article I investigate why two shows from different television genres in two different countries resort to nearly identical costume choices to convey villainy. I argue that that the directors, writers, and costume designers for the US science fiction showStargate SG1and BBC'sMerlinuse orientalist tropes of the veil as exotic, oppressed or threatening as costumes for their non-Muslim characters because of the centuries-long association in Western culture between Muslim veiling and the Other, while differentiating between acceptable and unacceptable headgear and face coverings. I draw on Said's Orientalism, Hall's Encoding/Decoding, medievalism, and the theory of the ethnonormative viewer to make this case. The “veil” has become an iconic negative sign in the West wholly distinct from meanings given to it by veiled Muslim women themselves. I suggest that anti-veiling ideology in Western publics stems in part from negative connotations given to it in television shows likeStargate SG1andMerlin.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".