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Record W4309756595 · doi:10.1177/14749041221125027

The colonial governmentality of Cambridge Assessment International Education

2022· article· en· W4309756595 on OpenAlexaff
David Golding, Kyle Kopsick

Bibliographic record

VenueEuropean Educational Research Journal · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsGovernmentalityColonialismSociologyLatin AmericansInternational educationSocial scienceComparative educationNeoliberalism (international relations)Political scienceHigher educationMedia studiesPoliticsLaw

Abstract

fetched live from OpenAlex

This study examines Cambridge Assessment International Education (CAIE) as a global assemblage that instrumentalizes colonial governmentality. CAIE is a department of the University of Cambridge that has governed schools in British colonies and former colonies since the mid-19th century. These schools constitute a Cambridge School system with approximately 1 million students around the world who take Cambridge examinations. CAIE invisibilizes its thousands of schools in the global South by enclosing them within privatized discursive spaces it terms “Cambridge School Communities.” CAIE simultaneously assembles and visibilizes an ecology of expertise by connecting a global array of researchers, consultants, businesses, organizations, publication outlets, and conferences. Rather than taking an interest in the “low-performing jurisdictions” of Africa, Latin America, and South Asia, CAIE’s ecology of expertise positions British educational culture in relation to a pre-modern “East.” CAIE explains the East’s high performance in international comparative assessments with stereotypes in order to reassert the superiority of British-led international education. These technologies of colonial governmentality altogether enable CAIE’s global extraction of epistemic authority.

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)0.005
metaresearch head score (Gemma)0.016
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.035
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.028
Scholarly communication0.0100.005
Open science0.0010.009
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.106
GPT teacher head0.499
Teacher spread0.393 · 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

Citations6
Published2022
Admission routes1
Has abstractyes

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