Minor Character, Minority Orientalisms, and the Borderlands of Asian America
Bibliographic record
Abstract
In Playing in the Dark: Whiteness and the Literary Imagination, Toni Morrison forcefully reveals how American literature’s representational terrain can be understood through the history of enslavement and oppression. Her paradigm is not only political; she also advances an innovative interpretive approach to American literature, encouraging us to take a closer look at racialized minor characters. An intellectual investment in the minor character helps generate comparative race critiques that expand how American literatures can be analyzed. Along these lines, this article focuses on a particular inclusion of a minor character, an Asian American female, within a Chicano literary production.1 In order to illuminate the importance of what we might call minority Orientalism, I explore the ways in which Alejandro Morales Wgures the futuristic Asian American subject within his speculative novel, The Rag Doll Plagues (1992).2 Although this article focuses on one book, my critical methodology and theorization can be applied much more broadly. An interpretation of minority Orientalist texts spotlights the Wgure of the Asian or Asian American as a minor character who functions to clarify the comparative and asymmetrical nature of racial exclusions. Some questions to consider: What is particularly unique about Chi cano literary Orientalism? Why do Chicano writers seem collectively invested in employing Asian and Asian American characters and con texts to Xesh out the Wctional world? Such questions can be unpacked by thinking interracially and interethnically: Chicanos and Asian Americans are two populations that have been linked historically through citizenship status, class, labor exploitation, and regional habitation. At various points in the nineteenth and twentieth centuries, the American
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".