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Record W4387970002 · doi:10.7311/0860-5734.32.1.06

“Fearing your own queer self”: Depictions of Diasporic Queer Experience in Grace Lau’s Poetry

2023· article· en· W4387970002 on OpenAlexaboutno aff
Joanna Antoniak

Bibliographic record

VenueAnglica An International Journal of English Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsQueerDiasporaPoetryGender studiesLesbianChinese americansIdentity (music)SociologyImmigrationHistoryLiteratureEthnic groupAestheticsArtAnthropology

Abstract

fetched live from OpenAlex

The intersection of migrant and queer experiences constitutes one of the core motifs of The Language We Were Never Taught to Speak (2021), the debut poetry collec- tion by Grace Lau, a Chinese Canadian poet. Through a series of interconnected vignettes, Lau provides an insight into her experiences as both a Canadian and a Chinese immigrant, a lesbian and a failed model child, an aficionado of traditional Chinese culture and an en- thusiast of contemporary Western popular culture. The mosaic of experiences illustrates the complexity and intricacy of the author’s identity/ies. Through the analysis of three poems (“The Levity,” “The Lies That Bind,” and “My Grief Is a Winter”), supported with references to the theoretical works on Asian North American writing and queer Asian mi- grant experience, the article discusses Lau’s depictions of queerness and her experiences as a Chinese immigrant in relation to the Canadian LGBTQ+ community, white queer liberalism, and internal politics of the Chinese diaspora. It proposes to see Lau’s poetry as an example of biomythography, a form of autobiographical writing showcasing how encounters with different communities shape the subject. In the process of disentangling her complex ties with the Chinese diaspora, the white Canadian LGBTQ+ community and her own family, Lau reveals the impact of her interactions with those different groups as she can finally express her identity as a queer Chinese Canadian.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.591
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.052
GPT teacher head0.357
Teacher spread0.305 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueAnglica An International Journal of English StudiesSame topicCanadian Identity and HistoryFrench-language works237,207