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Record W4392937379 · doi:10.18438/eblip30413

Plan S and Open Access (OA) in Quebec: What Does the Revised FRQ OA Policy Mean for Researchers?

2024· article· en· W4392937379 on OpenAlexafffundvenueabout
Rachel Harris, Jessica Lange, Pierre Lasou

Bibliographic record

VenueEvidence Based Library and Information Practice · 2024
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsUniversité LavalMcGill UniversityConcordia University
FundersCanadian Institutes of Health ResearchSimon Fraser University
KeywordsComputer sciencePlan (archaeology)Library scienceWorld Wide WebHistory

Abstract

fetched live from OpenAlex

Objective – Our article examines the effects of Quebec’s provincial funding agency (FRQ)’s revised 2022 OA policy on researchers. Following FRQ’s participation as a cOAlition S funding agency, which involves endorsing Plan S principles, we provide an overview of the OA options for researchers. We examine these options under the FRQ 2019 and FRQ 2022 policy years, account for the effect of transformative agreements (TA) on OA publishing options, as well as the financial implications for researchers under the revised policy. Methods – The researchers extracted a list of FRQ-funded publications from years 2020 to 2022 using the DOI registration agency Crossref. Using this sample set, the researchers quantitatively analyzed OA options under the previous policy and the revised one, comparing the two. To determine the effect of transformative agreements (TAs)s, we reviewed current agreements offered through Canada’s national licensing agency Canadian Research Knowledge Network (CRKN). Results ­– We found that the self-archiving method for open access (OA) is reduced under the revised 2022 policy. Our results lead us to anticipate the pressure felt by authors who will be required to pay article processing charges (APCs) to meet grant requirements. Conclusion – The current publishing patterns of FRQ-funded researchers are primarily concentrated in hybrid journals not covered by transformative agreements. As such, researchers will face additional financial costs should these publishing patterns continue. Concerted efforts among all stakeholders (researchers, universities, libraries, and funders) are needed to sustainably transition to immediate OA. French version – https://spectrum.library.concordia.ca/id/eprint/993806/

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)0.092
metaresearch head score (Gemma)0.203
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Open science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.996
Threshold uncertainty score0.938

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0920.203
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.011
Science and technology studies0.0100.012
Scholarly communication0.0210.009
Open science0.0040.005
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0060.001

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 head0.546
GPT teacher head0.598
Teacher spread0.052 · 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
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
Published2024
Admission routes4
Has abstractyes

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