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Record W4404993489 · doi:10.1080/02684527.2024.2433823

The “special relationship,” and the overseas Chinese: the Information Research Department (IRD) and the United States Information Agency (USIA) cold war partnership in East Asia, 1950s-1970s

2024· article· en· W4404993489 on OpenAlexfundno aff
Dalton Rawcliffe

Bibliographic record

VenueIntelligence & National Security · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicVietnamese History and Culture Studies
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCold warGeneral partnershipAgency (philosophy)Political scienceChinaEast AsiaSpecial RelationshipPublic administrationEconomic growthPoliticsSociologyLawEconomicsSocial science

Abstract

fetched live from OpenAlex

From the 1950s to the 1970s, Britain’s strategic role in the Cold War in East and Southeast Asia shaped the post-WWII contours and ramifications of what Winston Churchill famously dubbed the Anglo-American ‘special relationship’. Through its clandestine Information Research Department (IRD), Britain targeted anti-communist propaganda, focusing on neutral nations and the overseas Chinese communities. The IRD assessed communist influence among emigrant Chinese communities along with their views of the United States. The IRD served to support American goals while bolstering Britain’s regional influence. Despite occasional divergences, the IRD and the United States Information Agency (USIA) coordinated efforts to counter communist expansion, reflecting the adaptability of their ‘special relationship’.

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)0.004
metaresearch head score (Gemma)0.003
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: Empirical
Teacher disagreement score0.165
Threshold uncertainty score0.329

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0110.014
Scholarly communication0.0080.005
Open science0.0000.005
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.041
GPT teacher head0.359
Teacher spread0.318 · 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
Published2024
Admission routes1
Has abstractyes

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