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Record W2093912013 · doi:10.1108/07378830810880298

Consortia: anti‐competitive or in the public good?

2008· article· en· W2093912013 on OpenAlexaffabout
Catherine Maskell

Bibliographic record

VenueLibrary Hi Tech · 2008
Typearticle
Languageen
FieldComputer Science
TopicLibrary Collection Development and Digital Resources
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsPublishingElectronic publishingAcademic libraryScholarly communicationLibrary scienceBusinessWorld Wide WebComputer sciencePublic relationsPolitical scienceThe Internet

Abstract

fetched live from OpenAlex

Abstract Purpose – The purpose of this paper is to report on research that examined the potential affects of academic library consortia activity on the scholarly publishing cycle. Design/methodology/approach – Semi‐structured interviews of 30 university librarians from across Canada and representatives from six federal government agencies involved in university funding, copyright and competition policy, were used to examine consortia activity in the broad context of the scholarly publishing cycle from the competing perspectives of the market economy and the public good. The principles of competition and copyright were used to define the theoretical premise of the research. Findings – University librarians primarily see consortia activity as supporting academic libraries' public good role of providing access to information as equitably and as barrier‐free as possible. They saw consortia as more than just buying clubs, but also as a means for libraries to share resources and expertise. Federal government agency representatives saw consortia activity firmly anchored in the market economy, levelling the playing field between libraries and publishers, and providing libraries opportunities to leverage their budgets. Research limitations/implications – This research was unique to the Canadian situation of federal funding of universities and only a sampling of university librarians was feasible. Practical implications – The results show a need to educate librarians and government funding bodies and policy makers as to the goals and outcomes of consortia activity. Originality/value – At the time of the defence of the thesis this work had not been done before.

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)0.032
metaresearch head score (Gemma)0.066
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.979
Threshold uncertainty score0.170

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.066
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0100.022
Scholarly communication0.0210.013
Open science0.0020.010
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0140.001

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 head0.030
GPT teacher head0.212
Teacher spread0.182 · 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 designTheoretical or conceptual
Domainnot available
GenreCommentary

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
Published2008
Admission routes2
Has abstractyes

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