Revisiting Asian American Representations in Hollywood: Negotiating Identity, Gender, and Sexuality
Bibliographic record
Abstract
This research paper investigates representations of the Asian diaspora, gender, and sexuality by comparing two films Always Be My Maybe (Khan, 2019) and The Half of It (Wu, 2020), representative of a successful Hollywood trend marked by the 2020 (Parasite, Bong Joon-ho) and 2021 (Minari, Lee Isaac Chung) Oscar wins. The films counter a longstanding history of Orientalist Asian American tropes and stereotypes at a moment when China’s booming economy and domestic markets coincide with more creative directors of Asian origin telling their stories in Hollywood. Through close textual analysis of the two films narratives and comparison of their sequences, I examine how these films construct Asian diasporic identity, gender, and sexuality. The analysis demonstrates how racial identity, never fixed, is constantly in the process of construction shaped by larger social forces that respond to and negotiate dominant ideologies supporting certain stereotypes. In The Half of It race, gender, and sexuality are to a great extent reframed through subtlety and subversive characterization. Always Be My Maybe makes use of Hollywood conventions at least in part to shift the conventional narratives about Asians as it pertains to identity, gender, and sexuality.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".