Bibliographic record
Abstract
This study investigates how the queer codes in queer film posters are heterosexualized to fulfill a marketing strategy to maximize popularity. Twenty-two American, British and Canadian queer films screened in Korea were selected for a comparison of the original English film posters to their Korean counterparts. The patterns of variation in the queer codes were examined using the visual concepts of Kress and van Leeuwen (1996), including gaze, frame, salience, color, and layout. To analyze how the meanings of the original film posters are re-encoded by the translators, this study adopts Hall's (1980) encoding/decoding theory on “dominant-hegemonic reading,” “negotiated reading,” and “oppositional reading.” Generally, the Korean translated posters distorted the original meaning of the queer codes in the English film posters. The queer codes were changed to prevent the Korean posters from conflicting with domestic sentiment which is ill-disposed towards homosexuals. This shows that queer film posters are designed to attract more audiences the way general commercial films do. Thus, the queer codes in original English film posters are translated in their Korean counterparts to be re-encoded into a heterosexual point of view for marketing purposes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".