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Record W4416573854 · doi:10.1080/2201473x.2025.2592190

Chinese racialisation and colonial complicity: connecting capitalism, white supremacy and settler colonisation in Aotearoa

2025· article· en· W4416573854 on OpenAlexaboutno aff

Bibliographic record

VenueSettler Colonial Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsWhite supremacyColonisationColonialismAotearoaWhite (mutation)DecolonizationPostcolonialism (international relations)IndigenousPower (physics)

Abstract

fetched live from OpenAlex

Building on theorisations examining the colonial positionalities of Asian diasporic communities in settler societies such as Canada, Hawai’i and the U.S., this article investigates the role of Chinese racialisation and discursive positioning vis-à-vis Pākehā and Māori in bolstering, obscuring or otherwise entrenching White supremacy, settler colonisation, and capitalism in Aotearoa. Specifically, I offer a critical analysis of historical texts, building upon and expanding existing narratives within secondary sources through the theoretical framework of colonial racial capitalism. I argue that Chinese racialisation and discursive positioning in Aotearoa has and continues to be shaped by the material interests of ‘New Zealand’ as a settler-colonial project founded upon the subjugation of Māori land and life, and reliant on the alienation of racialised tauiwi from the national identity and body politic. At once a Yellow Peril, model minority and essentialised Other, Chinese immigrants have been differentially racialised and positioned in society in order to produce and reproduce the conditions necessary for the preservation of colonial racial capitalism. Our racialisation as Chinese people can then be understood as inseparable from the settler-colonial project, and so to resist against White supremacy thus also requires that we resist against the violences of capitalism and (settler) colonisation.

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
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.766
Threshold uncertainty score0.996

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 studies0.0050.001
Scholarly communication0.0000.000
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 head0.021
GPT teacher head0.357
Teacher spread0.336 · 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
Published2025
Admission routes1
Has abstractyes

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