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Record W4391305271 · doi:10.15173/a.v2i2.2999

I Love Asian Girls!; Orientalism through the Female Asian American Lens

2022· article· en· W4391305271 on OpenAlexaff
Natalie Chu

Bibliographic record

VenueAletheia · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsMcMaster University
Fundersnot available
KeywordsOrientalismAsian americansGender studiesLens (geology)HistorySociologyArtLiteratureAnthropologyBiologyEthnic groupPaleontology

Abstract

fetched live from OpenAlex

“My immigrant experience is not the same as these women, but I felt it in my bones. Because to be here is to be the same,” laments Eileen Cheng-Yin Chow, a professor of Asian American and diaspora studies at Duke University, following the Atlanta Spa killings. The sexualization of Asian women has persisted since their first arrival to the Americas in the 20th century. Not only has this caused direct violence, like the Atlanta Spa shooting in March 2021, which resulted in the death of 6 Asian women, but also the ‘orientalizing’ perception and self-perception of Asian American Women (AAW). In this paper, I explore the historical origins of this orientalization as it relates to media and then analyze contemporary art media (poetry, photography, etc.) from AAW to explore how this has affected modern self-perception. By focusing on the direct perspective of AAW, I explore different ways orientalism is synthesized through AAW identity, dissonance, fragmentation, and rebellion. Through my paper, I conclude that the intersectionality between orientalism, gender, and nationality has caused a profound disillusion from traditional and cultural expectations of the ‘homeland’ as well as disillusioned from the stereotypical expectations of the Americas. This, however, may contribute to the creation of a new identity, which hinges on the unique aspects of intersectionality, which focuses on the AAW voice instead of the colonial voice.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.714
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.029
GPT teacher head0.299
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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