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Record W7025896731

Национальная идентичность в современной китайской прозе

2017· article· ru· W7025896731 on OpenAlexaboutno aff

Bibliographic record

VenueDigital Library of the Belarusian State University (Belarusian State University) · 2017
Typearticle
Languageru
FieldMedicine
TopicBiomedical and Chemical Research
Canadian institutionsnot available
Fundersnot available
KeywordsZhàngBuddhismNational identityEthnic groupChinaIdentity (music)Syncretism (linguistics)Chinese buddhism
DOInot available

Abstract

fetched live from OpenAlex

Посвящена вопросу выявления национальной идентичности в современной китайской литературе. Исследование проведено с учетом особенностей китайского национального самосознания и характера, историзма, культурного синкретизма конфуцианской, даосской и буддистской традиций, природы китайской системы письма и понятия «вэнь». Очерчены различия между этнической и национальной идентичностями, а также проблема самоидентификации автора на примере китайской литературы зарубежья. Особое внимание уделяется изучению прозы китайского зарубежья на примере творчества современной писательницы Чжан Лин (1957). Теоретической базой исследования являются работы Г. Д. Гачева, М. Н. Корнилова, В. М. Пивоева, Н. А. Спешнева и др. = The article deals with the searching for national identity of contemporary Chinese literature, based on the historical thinking, peculiarities of the Chinese national self-consciousness, cultural syncretism of Confucian, Taoist and Buddhist traditions, specific features of Chinese national character, nature of the Chinese writing system, wen concept. The differences between ethnic and national identity is also regarded in this article along with the problem of author’s self-identification on the example of Overseas Chinese literature. Special attention is paid to the learning of Overseas Chinese literature’s prose. Besides, it focuses on the works by Zhang Ling (1957), one of well-known Chinese fiction writer in Canada. We address theoretical studies by G. D. Gachev, M. N. Kornilov, V. M. Pivoev, N. A. Speshnev.

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)0.003
metaresearch head score (Gemma)0.007
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: none
Teacher disagreement score0.026
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0050.011
Scholarly communication0.0130.006
Open science0.0010.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0260.009

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 head0.013
GPT teacher head0.204
Teacher spread0.191 · 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
Published2017
Admission routes1
Has abstractyes

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