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Record W2723469301 · doi:10.14288/cl.v0i227.187795

Waiting for Asian Canada: Fred Wah's Transnational Aesthetics

2016· article· en· W2723469301 on OpenAlexaboutno aff
Timothy Yu

Bibliographic record

VenueOpen Collections · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicAsian American and Pacific Histories
Canadian institutionsnot available
Fundersnot available
KeywordsDialogicChinaEthnic groupHistorySociologyPolitical scienceGenealogyGender studiesAnthropologyLaw

Abstract

fetched live from OpenAlex

Fred Wah's 1985 Waiting for Saskatchewan offers a snapshot of the emergence of an Asian Canadian aesthetic, providing a genealogy that positions Asian Canadian writing at the nexus of transnational flows from China, Japan, and the United States, while also emphasizing the cross-ethnic coalitions that give rise to the category of the Asian Canadian in the 1970s and 1980s. Waiting for Saskatchewan offers a complex constellation of Chinese content, Japanese forms, and U.S. aesthetic mediation that nonetheless takes as its “centre” a small Canadian prairie town. The forms of Waiting, from Olsonian projective poetics to the Japanese haibun, reveal Asian Canada as a process of transnational convergence, a dialogic space that is always being rewritten across national borders.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.073
Threshold uncertainty score0.529

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0370.019
Scholarly communication0.0090.003
Open science0.0010.004
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0090.001

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 head0.020
GPT teacher head0.273
Teacher spread0.253 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2016
Admission routes1
Has abstractyes

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