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Record W1603610212 · doi:10.1007/s11702-011-0145-7

A Dictionary of Maqiao: Metafiction of Collective Biography

2011· article· en· W1603610212 on OpenAlexaff
Ying Kong

Bibliographic record

VenueFrontiers of Literary Studies in China · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicChinese history and philosophy
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsBiographyLife writingLiteratureLexiconHistoryCollective memoryWitnessReading (process)SociologyLinguisticsArtPhilosophyPolitical scienceLaw

Abstract

fetched live from OpenAlex

In the field of life writing, a collective biography is a biography of a group of lives that share common background characteristics. Han Shaogong’s A Dictionary of Maqiao (1996) collects life stories, in a lexical list of entries, of 22 principal characters from the fictitious village of Maqiao. If there is a common background characteristic of Maqiao’s people, it is their special way of using words to shape their way of thinking. The 115 word entries that Maqiao people use reveal life stories covering more than a century. As a first person narrator and a biographer of collective lives, Han also seems to be a witness to their lives. How does he fuse autobiographical, biographical and historical truths into this text? How does he interpret Maqiao’s lexicon in the light of their collective lives? Are auto/biographical theories applicable to Han’s collective biography? Finally, what contributions does he make to collective life writing? To answer the above questions, this paper takes A Dictionary of Maqiao as a metafiction to discuss life writing issues with theorists such as Paul John Eakin, Philippe Lejeune, and Zhao Baisheng. It also searches for Han’s methodologies and techniques in creating collective life stories through a textual analysis. By reading literary biographies of Han Shaogong and his stories of Maqiao people, this paper also analyzes what constitutes “truths” and “facts” in this collective biography. Finally, it demonstrates how Han makes biography new in terms of life writing.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.755
Threshold uncertainty score0.380

Codex and Gemma teacher scores by category

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

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 head0.061
GPT teacher head0.307
Teacher spread0.245 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations1
Published2011
Admission routes1
Has abstractyes

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