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The Adoption of Open Access Funds Among Canadian Academic Research Libraries, 2008-2012

2014· article· en· W1937491128 on OpenAlexaffvenueabout
Crystal Hampson

Bibliographic record

VenuePartnership The Canadian Journal of Library and Information Practice and Research · 2014
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsScholarly communicationPublishingContext (archaeology)Public relationsBusinessService (business)InstitutionPolitical scienceLibrary scienceSociologyMarketingSocial scienceComputer science

Abstract

fetched live from OpenAlex

As a result of changes in scholarly communication created by the open access movement, some academic libraries established open access (OA) publishing funds. OA funds are monies set aside at an institution to fund open access publishing of the results of scholarly research. OA funds are a recent innovation in the type of services offered by academic libraries. Adoption of an innovation can be examined in the light of established theories of innovation adoption among social systems. To examine academic libraries’ responses to OA publishing charges, this article explores the adoption of OA funds among Canadian academic research libraries from 2008 to 2012 by analyzing results from a series of previously published surveys. The findings are then examined in light of Everett Rogers’ Innovation Diffusion Theory (IDT) to consider the question of whether or not OA funds are becoming a standard service in Canadian academic research institutions. Adoption in Canada is briefly compared to that in the United States and United Kingdom. The paper concludes that, as of 2012, OA funds were becoming common but were not a standard service in Canadian academic research libraries and that libraries were actively participating in the development of OA funding models. Given the current Canadian context, the need of researchers for OA publishing support is likely to create pressure for continued adoption of OA funds among Canadian academic research institutions. However, assessment of existing OA funds is needed.

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)0.118
metaresearch head score (Gemma)0.070
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Science and technology studies, Scholarly communication, Open science, Research integrity
Consensus categoriesMetaresearch, Bibliometrics, Scholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.789
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1180.070
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0240.043
Science and technology studies0.0040.002
Scholarly communication0.0310.098
Open science0.0060.001
Research integrity0.0000.002
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 head0.685
GPT teacher head0.603
Teacher spread0.083 · 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 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

Citations15
Published2014
Admission routes3
Has abstractyes

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