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Ye Si (也斯) (1949–2013)

2018· book-chapter· en· W4321463652 on OpenAlexaff
Yan Tang

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicHong Kong and Taiwan Politics
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsBachelorModernism (music)ArtPoetryChinese literatureComparative literatureHistoryArt historyMedia studiesChinaLiteratureSociology

Abstract

fetched live from OpenAlex

Leung Ping-kwan, MH (pen name: Ye Si) was an influential writer, essayist, and scholar in Hong Kong. He became a freelancer in the 1960s, and later obtained his Bachelor’s degree in English at Hong Kong Baptist University. In 1978, he was admitted to the Department of Comparative Literature at the University of California, San Diego. He completed the doctoral degree in 1984. His dissertation is entitled ‘Aesthetics of Opposition: A Study of the Modernist Generation of Chinese Poets, 1936–1949’. After returning to Hong Kong, he taught in the Department of English Studies and Comparative Literature at the University of Hong Kong. In 1998, he became a professor in the Chinese Department at Lingnan University in Hong Kong. Later on, he worked as the Director of the Centre for Humanities Research at Lingnan University, teaching film, comparative literature, and modernism among other subjects. As a prolific writer and scholar, he has published fiction, poetry, essays, as well as academic works on films, comparative literature, Chinese modernism, and literature in Hong Kong. He died on 5 January 2013.

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)0.000
metaresearch head score (Gemma)0.000
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.065
Threshold uncertainty score0.216

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0650.021

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 head0.302
Teacher spread0.262 · 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
Published2018
Admission routes1
Has abstractyes

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