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Record W4416544889 · doi:10.48550/arxiv.2505.12134

APC waivers and Ukraine's publishing output in Gold OA journals: Evidence from five commercial publishers

2025· preprint· en· W4416544889 on OpenAlexaboutno aff
Serhii Nazarovets

Bibliographic record

VenueBorys Grinchenko Kyiv University Institutional repository (Borys Grinchenko Kyiv University) · 2025
Typepreprint
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsnot available
Fundersnot available
KeywordsPublishingUkrainianBibliometricsQuarter (Canadian coin)Web of sciencePeriod (music)

Abstract

fetched live from OpenAlex

This study examines the effect of article processing charge (APC) waivers on the participation of Ukrainian researchers in fully Gold Open Access (Gold OA) journals published by the five largest academic publishers - Elsevier, SAGE, Springer Nature, Taylor & Francis, and Wiley - during the period 2019-2024. These publishers were selected because, in response to the full-scale war launched against Ukraine in 2022, all five introduced emergency 100% APC-waiver policies for Ukrainian authors. Using bibliometric data from the Web of Science Core Collection, the study analyses publication trends in Ukrainian-authored articles in fully Gold OA journals of these publishers before and after 2022. The results show a marked post-2022 increase in Ukraine's Gold OA output, particularly in journals published by Springer Nature and Elsevier. Disciplinary and publisher-specific patterns are evident, with especially strong growth in the medical and applied sciences. The findings underscore the potential of targeted support measures during times of crisis, while also illustrating the inherent limitations of APC-based publishing models in fostering equitable scholarly communication.

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)0.011
metaresearch head score (Gemma)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Bibliometrics, Science and technology studies, Scholarly communication, Open science, Research integrity
Consensus categoriesMeta-epidemiology (narrow), Bibliometrics, Scholarly communication, Open science, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.265
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0620.052
Science and technology studies0.0030.002
Scholarly communication0.0110.014
Open science0.0120.016
Research integrity0.0020.006
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 head0.360
GPT teacher head0.418
Teacher spread0.057 · 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 designObservational
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
Published2025
Admission routes1
Has abstractyes

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