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Record W2913265645 · doi:10.2777/836532

Future of scholarly publishing and scholarly communication report of the expert group to the European Commission

2019· article· en· W2913265645 on OpenAlexaff
Jean‐Claude Guédon, Michael Jubb, Bianca Kramer, Mikael Laakso, Birgit Schmidt, Elena Šimukovič, Jennifer Hansen, Robert Kiley, Anne Kitson, Wim van der Stelt, Kamilla Markram, Mark Patterson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSemantic Web and Ontologies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsScholarly communicationPublishingCommissionPolitical scienceEuropean commissionGroup (periodic table)Library scienceElectronic publishingInternet privacyPublic relationsWorld Wide WebMedia studiesComputer scienceSociologyLawBusinessEuropean unionThe Internet

Abstract

fetched live from OpenAlex

The report proposes a vision for the future of scholarly communication; it examines the current system -with its strengths and weaknesses- and its main actors. It considers the roles of researchers, research institutions, funders and policymakers, publishers and other service providers, as well as citizens and puts forward recommendations addressed to each of them. The report places researchers and their needs at the centre of the scholarly communication of the future, and considers knowledge and understanding created by researchers as public goods. Current developments, enabled primarily by technology, have resulted into a broadening of types of actors involved in scholarly communication and in some cases the disaggregation of the traditional roles in the system. The report views research evaluation as a keystone for scholarly communication, affecting all actors. Researchers, communities and all organisations, in particular funders, have the possibility of improving the current scholarly communication and publishing system: they should start by bringing changes to the research evaluation system. Collaboration between actors is essential for positive change and to enable innovation in the scholarly communication and publishing system in the future.

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)0.084
metaresearch head score (Gemma)0.075
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.974
Threshold uncertainty score0.447

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0840.075
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0070.008
Science and technology studies0.0040.004
Scholarly communication0.0260.010
Open science0.0050.006
Research integrity0.0200.007
Insufficient payload (model declined to judge)0.0070.003

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 head0.023
GPT teacher head0.250
Teacher spread0.227 · 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
Domainnot available
GenreReview

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

Citations88
Published2019
Admission routes1
Has abstractyes

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