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Record W1992101860 · doi:10.5860/crl.75.6.808

Do Open Access Electronic Theses and Dissertations Diminish Publishing Opportunities in the Sciences?

2014· article· en· W1992101860 on OpenAlexaff
Marisa Ramírez, Gail McMillan, Joan Dalton, Ann Hanlon, Heather S. Smith, Chelsea Kern

Bibliographic record

VenueCollege & Research Libraries · 2014
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsUniversity of Windsor
FundersUniversity of Wisconsin-Milwaukee
KeywordsDiscoverabilityPublishingElectronic publishingPublicationLibrary scienceOpen access publishingWork (physics)Political scienceOpen scienceWorld Wide WebSociologyComputer scienceEngineeringThe InternetPhysicsLaw

Abstract

fetched live from OpenAlex

In academia, there is a growing acceptance of sharing the final electronic version of graduate work, such as a thesis or dissertation, in an online university repository. Though previous studies have shown that journal editors are willing to consider manuscripts derived from electronic theses and dissertations (ETDs), faculty advisors and graduate students continue to raise concerns that online discoverability of ETDs negatively impact future opportunities to publish those findings. The current study investigated science journal policies on open access ETDs and found that more than half of the science journals responding (51.4%) reported that manuscripts derived from openly accessible ETDs are welcome for submission and an additional 29.1 percent would accept revised ETDs under certain conditions.

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)0.076
metaresearch head score (Gemma)0.476
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Scholarly communication, Open science
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.997
Threshold uncertainty score0.403

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0760.476
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.008
Science and technology studies0.0040.009
Scholarly communication0.0170.024
Open science0.0030.010
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0200.005

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 head0.908
GPT teacher head0.671
Teacher spread0.238 · 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 designObservational
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

Citations18
Published2014
Admission routes1
Has abstractyes

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