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Record W4409220690 · doi:10.1515/9789882202511

Power and Identity in the Chinese World Order

2003· book· en· W4409220690 on OpenAlexaboutno aff

Bibliographic record

VenueHong Kong University Press eBooks · 2003
Typebook
Languageen
FieldSocial Sciences
TopicInternational Relations and Foreign Policy
Canadian institutionsnot available
Fundersnot available
KeywordsIdentity (music)Power (physics)Order (exchange)SociologyArtEconomicsAestheticsPhysics

Abstract

fetched live from OpenAlex

Wang Gungwu is one of the most influential historians of his generation. Initially renowned for his pioneering work on the structure of power in early imperial China, he is more widely known for expanding the horizons of Chinese history to include the histories of the Chinese and their descendents outside China. It is probably no coincidence, Philip Kuhn observes, that the most comprehensive historian of the Overseas Chinese is the historian most firmly grounded in the history of China itself. This book is a celebration of the life, work, and impact of Professor Wang Gungwu over the past four decades. It commemorates his contribution to the study of Chinese history and the abiding influence he has exercised over later generations of historians, particularly in the Asia-Pacific region. The book begins with an historiographical survey by Philip Kuhn (Francis Lee Higginson Professor of History at Harvard University) of Wang Gungwu’s enduring contribution to scholarship. It concludes with an engaging oral history of Professor Wang’s life, career, and research trajectory. The intervening chapters explore many of the fields in which Wang Gungwu’s influence has been felt over the years, including questions of political authority, national identity, commercial life, and the history of the diaspora from imperial times to the present day. Each of these chapters is authored by a former student of Professor Wang, now working and teaching in Hong Kong, Southeast Asia, Australasia, Taiwan and Canada. The contributors to this book are: Adrian CHAN, James K. CHIN, Antonia FINNANE, John FITZGERALD, Edmund S., K. FUNG, HO Hon-wai, HUANG Jianli, Jennifer W. JAY, Philip A. KUHN, LEE Guan-kin, Jane LEE, LEE Kam-keung, Terry NARRAMORE, NG Chin-keong, SO Wai-chor, Billy K. L. SO

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: Other · Consensus signal: Other
Teacher disagreement score0.115
Threshold uncertainty score0.229

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 studies0.0100.014
Scholarly communication0.0080.003
Open science0.0000.003
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 head0.014
GPT teacher head0.281
Teacher spread0.267 · 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
GenreOther

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
Published2003
Admission routes1
Has abstractyes

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