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Record W4399726278 · doi:10.3138/chr-2022-0030

Anti-Chinese Racism and the Structure of White Supremacy: An Anti-essentialist Antiracist Perspective on Canadian History

2024· article· en· W4399726278 on OpenAlexaffvenueabout
Timothy J. Stanley

Bibliographic record

VenueCanadian Historical Review · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsEssentialismRacismWhite supremacyPerspective (graphical)Gender studiesWhite (mutation)SociologyArtGeneticsBiology

Abstract

fetched live from OpenAlex

Racisms are among the social structures that shaped Canada’s past and are shaping Canada’s present. Anti-essentialist antiracism accounts for these structures by recognizing that there are many different racisms, but all racisms meet conditions of racialization, of the organization of racializations into exclusions, and of the enactment of negative consequences on the excluded. These conditions lead to strategies for antiracist research, which are key to rebuilding the linkages between people that racisms destroy. This paper builds a theoretically informed argument while examining the historical and present-day experiences of Chinese Canadians. Engaging with present-day realities, moving beyond common-sense explanations that individualize racism, and building on the sources of the racialized and excluded make evident the structure of racism. Chinese language sources document the “apartheiding” of Canada and its effects. They also enable the dialogical re-reading of dominant sources to pinpoint moments of organizing this structure into the world. Today, historically produced cultural narratives and the cultural landscapes of modern cities mark those racialized as Chinese as people who either do not belong or whose presence needs explanation. These narratives and landscapes are the products of the anti-Chinese racism that was built into the settler colonialism that made Canada.

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.936
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.270
Teacher spread0.257 · 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 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

Citations2
Published2024
Admission routes3
Has abstractyes

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