MétaCan
Menu
Back to cohort
Record W2979871568 · doi:10.5446/51333

Bridging the Gap: Best Practices for OA Journals Articulating Policies for Open Repository Archiving

2017· article· en· W2979871568 on OpenAlexaff
Leah Vanderjagt

Bibliographic record

VenueTIB KMO / FLOWWORKS GmbH · 2017
Typearticle
Languageen
FieldComputer Science
TopicResearch Data Management Practices
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPublicationSession (web analytics)Scholarly communicationPublishingInstitutional repositoryOpen scienceWorld Wide WebBest practiceLibrary scienceOpen dataComputer sciencePublic relationsPolitical scienceBusinessInternet privacyAdvertising

Abstract

fetched live from OpenAlex

Although it may seem an implicit truth that open access journals exchange their content easily with open repositories (institutional or disciplinary), in practice, those who manage open repositories often have difficulty locating, identifying and interpreting the sharing policies of open access journals. This results in blockers and inefficiencies in bringing OA content into open repositories - which are environments can significantly increase the visibility of openly accessible research. Recent research by Schlosser (Schlosser, M., (2016). Write up! A Study of Copyright Information on Library-Published Journals. Journal of Librarianship and Scholarly Communication. 4, p.eP2110) revealed that 76% of journals in an analyzed sample in a mostly-OA set of journals did not have clear copyright articulation or sharing policies. This session will make recommendations to journal editors about articulating open archiving policies on journal websites. Furthermore, this session will also suggest strategies for institutional repository managers and open journal systems/library publishing managers at academic libraries to collaborate to inform journal editorial boards about the existence of open repositories, and help promote best practices for sharing content with these sites of open research discovery.

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)0.006
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication, Open science
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.822
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.000
Scholarly communication0.0410.036
Open science0.0090.005
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 head0.351
GPT teacher head0.486
Teacher spread0.135 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueTIB KMO / FLOWWORKS GmbHSame topicResearch Data Management PracticesFrench-language works237,207