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Record W6964033820 · doi:10.21428/1bfadeb6.53bb799e

Mapping the World of Library Publishing: Unveiling the Global Landscape and Collaboration behind the Scenes

2024· article· en· W6964033820 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicLibrary Collection Development and Digital Resources
Canadian institutionsLakehead University
Fundersnot available
KeywordsPublishingPresentation (obstetrics)Work (physics)Key (lock)Electronic publishingProject commissioning

Abstract

fetched live from OpenAlex

This article is derived from the presentation titled “Mapping the World of Library Publishing: Revealing the Global Landscape and Collaborative Efforts” delivered during the panel discussion “Working Together to Expand Library Publishing Globally” at the World Library and Information Congress (WLIC) 88th IFLA General Conference and Assembly on August 22, 2023, held in Rotterdam, The Netherlands. It provides insights into the background and collaborative dynamics among key stakeholders, including the IFLA Library Publishing Special Interest Group, the Library Publishing Coalition, and various international entities working behind the scenes of the Global Library Publishing Map project. The article delves into the project’s development, presenting a comprehensive analysis of all participating libraries and other organizations to unveil the global library publishing landscape as visualized on the Map. Moreover, it addresses the challenges encountered during the creation and maintenance of this Map. Finally, the paper explores the future directions and ongoing work in this important endeavor.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.867
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0080.005
Open science0.0010.000
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 head0.018
GPT teacher head0.216
Teacher spread0.197 · 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