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Record W2298525665 · doi:10.1629/uksg.278

Making OA monographs happen: Library-Press collaboration at the University of Ottawa, Canada

2016· article· en· W2298525665 on OpenAlexaffabout
Tony Horava

Bibliographic record

VenueInsights the UKSG journal · 2016
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsScholarshipPublicationContext (archaeology)Library scienceScholarly communicationGeneral partnershipRevenuePolitical scienceOrder (exchange)CitationPublishingComputer scienceBusinessHistoryLaw

Abstract

fetched live from OpenAlex

At the University of Ottawa, Canada, the UO Press and the UO Library have developed a strategic partnership to publish and disseminate selected new monographs as gold open access (OA). Starting in 2013, the Library agreed to fund three books at C$10,000 per book (a total of C$30,000 per year) in order to remove barriers to accessing scholarship and to align with scholarly communication goals of the University. In 2015 this agreement was renewed for another three years and the funding was increased to cover four books (a total of C$40,000 per year). Ten titles have so far been published under this model. The data reveals that there have been 12,629 downloads as well as 16,584 page views of these titles, as of September 2015. There have been over 4,700 copies (print and EPUB) sold in spite of the free availability of the PDF version. This program has been very successful in terms of increasing the visibility and impact of the Press’s publications; in providing unrestricted access to new scholarly research; and also in providing a significant source of revenue for the Press. The goals, process and outcomes are described in the context of the UO Press and the UO Library.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.043
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.298
GPT teacher head0.427
Teacher spread0.129 · 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 teacher head, 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

Citations2
Published2016
Admission routes2
Has abstractyes

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