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Record W3044885408 · doi:10.5539/elt.v13n8p152

Tuhaos with Hongbaos are Going to the English World: Study on the Features of Chinese English Neologisms Based on Web

2020· article· en· W3044885408 on OpenAlex
Zongwei Song

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEnglish Language Teaching · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicLexicography and Language Studies
Canadian institutionsnot available
FundersSichuan University
KeywordsNeologismThe InternetChinaVariety (cybernetics)LinguisticsEnglish languageInflectionPsychologyHistoryWorld Wide WebComputer scienceArtificial intelligencePhilosophy

Abstract

fetched live from OpenAlex

This article discusses the features, reasons, and values of the mushrooming Chinese English neologisms (CENs). Generally speaking, CENs are a variety of English words, namely Chinese English words, some of which have entered Oxford English Dictionary (OED). Based on data from Web Corp Live, the author finds that: (1) CENs take on the grammatical and morphological characteristics of English words, such as inflection and derivation, which are not found in the previous related studies; (2) CENs belong specific semantic domains, which are closely related to China’s latest social, economic, cultural development in the network era. CENs are the production of language contact between Chinese and English in the time of Internet. CENs possess important values to observe or understand Chinese new social phenomena and to promote the communications between the Chinese and the English world.

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.

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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.134
Threshold uncertainty score0.916

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.014
GPT teacher head0.232
Teacher spread0.218 · 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