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Record W2937052695 · doi:10.3138/jsp.50.3.03

CJK Languages or English: Languages Used by Academic Journals in China, Japan, and Korea

2019· article· en· W2937052695 on OpenAlex

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

VenueJournal of Scholarly Publishing · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicComputational and Text Analysis Methods
Canadian institutionsnot available
Fundersnot available
KeywordsChinaEnglish languageMetadataLibrary scienceHistoryComputer scienceWorld Wide WebMathematics educationPsychology

Abstract

fetched live from OpenAlex

For this study, we searched academic journal databases and journal lists from China, Japan, and Korea, dating up to July 2018, to determine the percentage of domestic journals published in English in these three East Asian countries. This study differs from most previous studies that relied on article indexes and abstracts for determining the language of academic journals. We took advantage of the full-text searching capabilities that online journal archives allow. We found that journals labelled ‘English-Japanese mixed’ or ‘Korean and English’ typically have only English metadata and not English articles and that the vast majority of domestic journals in China, Japan, and Korea are still published in the national language with no English full text. Due to China’s fast development and its low percentage of English journals, the world may experience, for the first time in nearly a century, a decrease in the worldwide percentage of active academic journals published in the English language.

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)0.012
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.127
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0090.033
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.377
Teacher spread0.340 · 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