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Record W3196914484 · doi:10.17161/jcel.v5i1.14920

Canadian Collaborations: Library Communications and Advocacy in the time of COVID-19

2021· article· en· W3196914484 on OpenAlexaffabout
Christina Winter, Mark Swartz, Victoria Owen, Ann Ludbrook, Brianne Selman, Robert Tiessen

Bibliographic record

VenueJournal of Copyright in Education & Librarianship · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Administration
Canadian institutionsUniversity of WinnipegUniversity of TorontoToronto Metropolitan UniversityQueen's UniversityUniversity of CalgaryUniversity of Regina
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Face (sociological concept)Pandemic2019-20 coronavirus outbreakDigital libraryPublic relationsWorld Wide WebPosition (finance)Copyright lawBusinessSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Political scienceInternet privacyIntellectual propertyComputer scienceSociologyLawMedicine

Abstract

fetched live from OpenAlex

The COVID-19 pandemic forced libraries to unexpectedly and suddenly close their physical locations, necessitating a remote working environment and a greater reliance on digital and virtual services. While libraries were in a better position than most sectors due to decades of experience in licensing and acquiring digital content and offering virtual services such as chat reference, there still were some services and resources that traditionally had only been offered in a face-to-face environment, or were available in print only. There were questions in the Canadian library community about how, and if these programs could be delivered online and comply with Canadian copyright law. This article will describe the access and copyright challenges that Canadian libraries faced during the first nine months of the pandemic and will outline the collaborative efforts of the Canadian library copyright community to respond to these challenges.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.745
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.004
Open science0.0010.000
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 head0.048
GPT teacher head0.340
Teacher spread0.292 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2021
Admission routes2
Has abstractyes

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