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Record W6913024617 · doi:10.5683/sp3/sdfzuo

Library publishing and hosting in Canada - Institutional responses to a 2022 questionnaire

2023· dataset· en· W6913024617 on OpenAlexaffabout

Bibliographic record

VenueBorealis · 2023
Typedataset
Languageen
FieldEnvironmental Science
TopicHeavy Metal Exposure and Toxicity
Canadian institutionsUniversity of New BrunswickUniversity of Alberta
Fundersnot available
KeywordsPublishingStaffingDirectoryElectronic publishingAcademic libraryInformation system

Abstract

fetched live from OpenAlex

This dataset contains responses to an institutional questionnaire distributed to Canadian academic libraries with journal publishing or hosting programs. The questionnaire was conducted in both French and English, and distributed to 42 libraries identified by the authors as having programs or services in place to support journal publishing activities. 35 institutions responded between August 31, 2022 and October 20, 2022. Resulting data were cleaned and translated into English. This dataset contains information about services offered by library publishing and hosting programs, the number and types of journals being supported, and infrastructure and staffing models. We have reused and modified several questions from the 2022 Library Publishing Directory questionnaire, created by the Library Publishing Coalition and licensed under CC-BY-4.0.

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)0.004
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.996
Threshold uncertainty score0.354

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.024
Science and technology studies0.0040.001
Scholarly communication0.0040.001
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0630.019

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 head0.015
GPT teacher head0.228
Teacher spread0.214 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations1
Published2023
Admission routes2
Has abstractyes

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