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Record W7071383307

Shenzheners : stories

2016· article· en· W7071383307 on OpenAlexaboutno aff

Bibliographic record

VenueDigital Commons - Lingnan (Lingnan University) · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicHong Kong and Taiwan Politics
Canadian institutionsnot available
Fundersnot available
KeywordsGirlCommunismCapitalismMetropolitan areaChinaWork (physics)Theme (computing)
DOInot available

Abstract

fetched live from OpenAlex

Sterk translates the literary work "Shenzheners" 《出租車司機》, written by Xue Yiwei (薛憶溈). Contents include: The Country Girl (村姑), The Peddler (小販), The Physics Teacher (物理老師), The Dramatist (劇作家), The Two Sisters (兩妹妹), The Prodigy (神童), Mother (母親), Father (父親), The Taxi Driver (出租車司機).\nThe first book in English by acclaimed Chinese-Canadian writer Xue Yiwei, Shenzheners is inspired by the young city of Shenzhen, a market town north of Hong Kong that became a Special Economic Zone in 1980 as an experiment in introducing capitalism to Communist China. A city in which everyone is a newcomer, Shenzhen has grown astronomically to become a major metropolitan centre. Hailed as a Chinese Dubliners, the original collection was named one of the Most Influential Chinese Books of the Year in 2013, with most of the stories appearing in Best Chinese Stories.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0130.005
Scholarly communication0.0050.004
Open science0.0010.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0210.003

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 head0.027
GPT teacher head0.247
Teacher spread0.220 · 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 designQualitative
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
Published2016
Admission routes1
Has abstractyes

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