Re-ornamenting Asian Femininity: Ornamentalism as Opportunity in Representations of Asian Women in High-tech Popular Media
Bibliographic record
Abstract
The Asian woman has historically been objectified and fetishized in popular media and visual culture, and is portrayed as an expendable, hypersexualized object of desire (Cheng, 2019). Despite the notions of desire and fetish attached to Asian women, Asian femininity remains underexplored in studies of race and gender. Cheng (2019) explores the intertwining notions of corporeality and objecthood associated with Asian femininity and proposes the theory of Ornamentalism as a way of understanding the Asian woman's negotiation of her existence. Through a visual social semiotic analysis of 40 samples of promotional materials from three East Asian musical artists, this study explores the ways in which high-tech and AI-mediated media representations may allow Asian women to assert and establish visibility despite objectification, through the lens of Cheng's (2019) theory of Ornamentalism.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.016 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".