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Record W2123887376 · doi:10.1017/s0026749x14000365

Surveying Hong Kong in the 1950s: Western humanitarians and the ‘problem’ of Chinese refugees

2014· article· en· W2123887376 on OpenAlexaff
Laura Madokoro

Bibliographic record

VenueModern Asian Studies · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicHong Kong and Taiwan Politics
Canadian institutionsMcGill University
Fundersnot available
KeywordsRefugeeChinaMainland ChinaPolitical scienceOppressionPoliticsCommunismSpanish Civil WarPopulationGender studiesGeographyDevelopment economicsSociologyLawDemography

Abstract

fetched live from OpenAlex

Abstract At the end of the Second World War, there were over a million displaced persons and refugees in Europe alone. Hundreds of thousands of people were uprooted with the expansion of the Japanese empire across the Pacific Theater, and many others were similarly displaced when Japan was defeated. Others later fled civil conflicts, in South Asia, for instance, and in China, where thousands left the mainland during the final days of the Chinese Civil War. Among this massive displacement in Asia, unlike in Europe, only a few groups were identified as refugees. One such group consisted of the migrants in Hong Kong who, after 1949, were understood to be refugees fleeing communist oppression in the People's Republic of China. This article examines the critical role that surveys (population studies designed to account for, and define, refugee groups) played in shaping particular, Westernized Cold War understandings of the refugee experience in Hong Kong. These surveys were organized by non-state interests and undertaken with financial support from major American philanthropies. In examining the objectives and methodologies of the refugee surveys conducted in Hong Kong in the early 1950s, in contrast with studies undertaken contemporaneously in Europe, this article observes that, although at the time the flaws in the surveys were recognized and regularly disregarded in the pursuit of broad political objectives, scholars have failed to adequately recognize the subjective nature of the surveys' supposedly empirical evidence. As a result, the dominant European-based narrative about modern refugees has obfuscated the distinctive aspects of the refugee experience in Hong Kong.

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)0.006
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: Empirical
Teacher disagreement score0.206
Threshold uncertainty score0.409

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.004
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.340
Teacher spread0.310 · 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

Citations8
Published2014
Admission routes1
Has abstractyes

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