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Record W4386722840 · doi:10.5281/zenodo.8343804

Scaling up open access publishing through transformative agreements: results from 2019 to 2022

2023· report· en· W4386722840 on OpenAlexaboutno aff
Ciaran Hoogendoorn, Gaynor Redvers‐Mutton

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2023
Typereport
Languageen
FieldDecision Sciences
TopicAcademic Publishing and Open Access
Canadian institutionsnot available
Fundersnot available
KeywordsTransformative learningScalingPublishingPolitical scienceMathematicsPsychologyLaw

Abstract

fetched live from OpenAlex

The Biochemical Society provides a comparative case study showing the results of the transitioning of its journals to open access (OA) in three key publishing regions: 1. the UK and Australasia, 2. USA and Canada and 3. China. We wanted to test our theory that institutionally-funded OA through transformative agreements (TAs) delivers sustainable growth more successfully than author-funded OA via article publishing charges (APCs). Over a 4-year period from 2019 to 2022 we were able to chart the effects of different national and institutional levels of support for OA. Through concerted and strategic action at a national level by library consortia groups – Jisc in the UK, and CAUL in Australia and New Zealand – OA has shifted to become the predominant route of publication in this region of our study. Our data indicate that North America, behind this curve by a few years, is moving in a similar direction with higher uptake of OA in 2022. In contrast, OA publishing from China which at the start of the study represented the region with the highest OA output across our portfolio shows a dramatic decline. We believe this volatility may be a result of a lack of OA policy guidance, overreliance on the APC model, academic malpractice, as well as a lack of TAs which might otherwise support a more stable and diverse OA publishing output.

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)0.028
metaresearch head score (Gemma)0.116
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesScholarly communication, Open science, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.285
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0280.116
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.006
Science and technology studies0.0050.000
Scholarly communication0.1280.026
Open science0.0430.037
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0240.031

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 head0.464
GPT teacher head0.490
Teacher spread0.026 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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