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Record W1489557032 · doi:10.3386/w13849

The Higher Educational Transformation of China and Its Global Implications

2008· preprint· en· W1489557032 on OpenAlexaff
Yao Amber Li, John Whalley, Shunming Zhang, Xiliang Zhao

Bibliographic record

VenueNational Bureau of Economic Research · 2008
Typepreprint
Languageen
FieldSocial Sciences
TopicHigher Education Governance and Development
Canadian institutionsWestern University
Fundersnot available
KeywordsTransformation (genetics)ChinaGeographyChemistryArchaeology

Abstract

fetched live from OpenAlex

This paper documents the major transformation of higher education that has been underway in China since 1999 and evaluates its potential global impacts. Reflecting China's commitment to continued high growth through quality upgrading and the production of ideas and intellectual property as set out in both the 10th (2001-2005) and 11th (2006-2010) five-year plans, this transformation focuses on major new resource commitments to tertiary education and also embodies significant changes in organizational form. This focus on tertiary education differentiates the Chinese case from other countries who earlier at similar stages of development instead stressed primary and secondary education. The number of undergraduate and graduate students in China has been grown at approximately 30% per year since 1999, and the number of graduates at all levels of higher education in China has approximately quadrupled in the last 6 years. The size of entering classes of new students and total student enrollments have risen even faster, and have approximately quintupled. Prior to 1999 increases in these areas were much smaller. Much of the increased spending is focused on elite universities, and new academic contracts differ sharply from earlier ones with no tenure and annual publication quotas often used. All of these changes have already had large impacts on China's higher educational system and are beginning to be felt by the wider global educational structure. We suggest that even more major impacts will follow in the years to come and there are implications for global trade both directly in ideas, and in idea derived products. These changes, for now, seem relatively poorly documented in literature.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0020.003
Scholarly communication0.0030.003
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.203
GPT teacher head0.523
Teacher spread0.320 · 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 designObservational
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

Citations67
Published2008
Admission routes1
Has abstractyes

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