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Record W7045337517

Asian Canadian writing beyond autoethnography

2008· article· en· W7045337517 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicStructural Engineering and Materials Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsAutoethnographyEthnographyOpposition (politics)Ethnic groupIdeologyCultural conflictRacism
DOInot available

Abstract

fetched live from OpenAlex

"Asian Canadian Writing Beyond Autoethnography explores some of the latest developments in the literary and cultural practices of Canadians of Asian heritage. While earlier work by ethnic, multicultural, or minority writers in Canada was often concerned with immigration, the moment of arrival, issues of assimilation, and conflicts between generations, literary and cultural production in the new millennium no longer focuses solely on the conflict between the Old World and the New or the clashes between culture of origin and adopted culture. No longer are minority authors identifying simply with their ethnic or racial cultural background in opposition to dominant culture." "The essays in this collection explore ways in which Asian Canadian authors and artists have gone beyond what Francoise Lionnet calls autoethnography, or ethnographic autobiography. They demonstrate the ways representations of race and ethnicity, particularly in works by Asian Canadians in the last decade, have changedhave become more playful, untraditional, aesthetically and ideologically transgressive, and exciting."--BOOK JACKET.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.089
Threshold uncertainty score0.384

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0260.008
Scholarly communication0.0080.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.001

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 head0.006
GPT teacher head0.170
Teacher spread0.164 · 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 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
Published2008
Admission routes1
Has abstractyes

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