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Model(s) of the future? Overlay journals as an overlooked and emerging trend in scholarly communication

2023· article· en· W4314447480 on OpenAlex
Gail M. Thornton, Emily Kroeker

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Journal of Information and Library Science · 2023
Typearticle
Languageen
FieldDecision Sciences
TopicAcademic Publishing and Open Access
Canadian institutionsUniversity of Alberta
FundersQueen's UniversityUniversity of Texas at AustinHarvard University
KeywordsPreprintOverlayPublishingMaturity (psychological)Scholarly communicationPeer reviewCoronavirus disease 2019 (COVID-19)Overlay networkComputer sciencePsychologyWorld Wide WebPolitical scienceDiseaseMedicineThe Internet

Abstract

fetched live from OpenAlex

Abstract: Overlay journals, a potentially overlooked model of scholarly communication, have seen a resurgence due to the increasing number of preprint repositories and preprints on coronavirus disease 2019 (COVID-19) related topics. Overlay journals at various stages of maturity were examined for unique characteristics, including whether the authors submitted their article to the journal, whether the peer reviews of the article were published by the overlay journal, and whether the overlay journals took advantage of opportunities for increased discovery. As librarians and researchers seek new, futuristic models for publishing, overlay journals are emerging as an important contribution to 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.

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)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.331
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0040.077
Open science0.0020.000
Research integrity0.0000.000
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 head0.049
GPT teacher head0.332
Teacher spread0.283 · 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