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Record W4408386221 · doi:10.1002/asi.24989

What's in a name? Scholarly journal title changes and the quest for international visibility (1965–2020)

2025· article· en· W4408386221 on OpenAlexaff
Mahdi Khelfaoui, Yves Gingras

Bibliographic record

VenueJournal of the Association for Information Science and Technology · 2025
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsUniversité du Québec à MontréalUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsAudience measurementInternationalizationVisibilityImpact factorScopusPolitical scienceLibrary scienceScientometricsOrder (exchange)Scholarly communicationHistoryMedia studiesPublishingSocial scienceSociologyLawGeographyComputer scienceBusiness

Abstract

fetched live from OpenAlex

Abstract Scholarly journals have been de‐nationalizing and anglicizing their names for the past six decades in order to gain international visibility and facilitate their indexation in major international databases. Using the Web of Science, we analyzed the historical evolution of this trend and its geography, showing that it has been particularly concentrated in a few countries at different periods of time. Then, we evaluated how title changes have affected the evolution of the journals' language of publication, authorship, readership, and impact. The acceleration of the trend toward the de‐nationalization and anglicization of journal titles coincided with the rise of discourses on internationalization in the 1980s and the growing use, a decade later, of quantitative indicators in research evaluation, above all the impact factor. In general, this rebranding strategy of scholarly journals resulted in a higher visibility in the global market of scientific publications, leading to a more internationalized authorship and readership, but to the detriment of the use of national languages.

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)0.037
metaresearch head score (Gemma)0.109
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.777
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0370.109
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0090.018
Science and technology studies0.0000.000
Scholarly communication0.0030.004
Open science0.0010.000
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 head0.123
GPT teacher head0.493
Teacher spread0.369 · 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; both teacher heads agree on what is shown here.

Study designOther design
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

Citations2
Published2025
Admission routes1
Has abstractyes

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