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Record W6912998185 · doi:10.5281/zenodo.7180737

The Oligopoly's Shift to Open Access Publishing: How For-Profit Publishers Benefit from Gold and Hybrid Article Processing Charges

2022· article· en· W6912998185 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicPublishing and Scholarly Communication
Canadian institutionsUniversité de MontréalUniversity of Ottawa
Fundersnot available
KeywordsPublishingStatus quoTransformative learningRevenueAcademic communityScholarly communicationPreference

Abstract

fetched live from OpenAlex

The oligopoly’s revenues from gold and hybrid APCs continue to increase, demonstrating a strong source of profits at the cost of authors, and like previous studies demonstrate, their control of the scholarly publishing market. Instead of making scholarly publishing sustainable and accessible for all, exorbitant APCs (and more recently transformative agreements) preserve the status quo of the academic publishing market. The author-pays model excludes large parts of the academic community from publishing, giving preference to well-funded authors, disciplines and countries. Instead of removing barriers from academic publishing, OA APCs have shifted inequities from readers to authors, often affecting those same individuals.

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)0.003
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication, Open science
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.999
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0030.007
Scholarly communication0.0140.011
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0230.002

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 head0.108
GPT teacher head0.286
Teacher spread0.178 · 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.

Study designNot applicable
DomainEvaluation
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
Published2022
Admission routes1
Has abstractyes

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