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Record W2942716887 · doi:10.1163/15692108-12341408

Sowing Dragon’s Teeth and Harvesting Fleas? – A Historical Inquiry into China’s Education-Aid Programs since the 1970s

2018· article· en· W2942716887 on OpenAlexaff
Yun Liu

Bibliographic record

VenueAfrican and Asian Studies · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsQueen's University
Fundersnot available
KeywordsChinaMainstreamAsian studiesPolitical scienceEconomic growthVariety (cybernetics)Public administrationSociologyDevelopment economicsEconomicsLaw

Abstract

fetched live from OpenAlex

Abstract This paper reviews the historical evolution of China’s education-aid programs. These specific programs are seemingly consistent with China’s education reform legacy. With a cross-disciplinary survey regarding how foreign-aid policy commitments got delivered, the paper proposes more inclusive approaches for interpreting local contexts relevant to China’s education-aid policies. The following discussion first presents local evidence to provide plausible explanations from the national background of China’s social-economic reforms since the 1970s. Then it gives a case study of Wuhan, the provincial capital of Hubei, to examine how the local higher-education institutions have managed those education-aid practices since the late 1990s. Re-visiting a variety of mainstream views on China’s evolving national identity as a member of the Global South, the article ends by making some analysis of significance to the evolution of China’s education-aid policies.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.104
Threshold uncertainty score0.207

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0040.005
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.048
GPT teacher head0.345
Teacher spread0.296 · 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
Published2018
Admission routes1
Has abstractyes

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Same venueAfrican and Asian StudiesSame topicInternational Development and AidFrench-language works237,207