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Manitoba Public Libraries Response to the Early Stages of COVID-19

2021· article· en· W3180163338 on OpenAlexaffvenueabout
Kerry Macdonald, Andrew Robert, Breanne Bannerman-Gobeil, Richard Bee, Alan Chorney, Caralie Heinrichs, Stacey Lee, Kelly Murray, Melanie Sucha

Bibliographic record

VenuePartnership The Canadian Journal of Library and Information Practice and Research · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Administration
Canadian institutionsBrandon UniversityUniversity of ManitobaRed River College
Fundersnot available
KeywordsStaffingPandemicCoronavirus disease 2019 (COVID-19)Library sciencePublic relationsService (business)Public healthOrder (exchange)Political scienceBusinessMedicineComputer scienceNursingMarketingLaw

Abstract

fetched live from OpenAlex

Like many libraries across Canada, Manitoba public libraries have grappled with the challenges that COVID-19 has presented. Libraries have struggled to remain operational and offer a high level of service to patrons within the constraint of public health orders, all the while ensuring the safety and employment of their staff. Within the ever-changing environment of COVID-19, the Manitoba Library Association recognized the need to gather information from the library community in order to better position themselves to lend support and in an attempt to bridge information gaps. This article describes a study conducted by the Manitoba Library Association whereby fifty-five Manitoba public libraries were surveyed to identify how they were responding to COVID-19 and what their needs might be. The survey questions were divided into 6 sections (facilities, services, communications, staffing, connecting, wrap-up) and the results provide information and insight into how the Manitoba library community has dealt with the pandemic. More importantly, the results can serve to guide other libraries in decision-making and preparation for a pandemic.

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)0.006
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.817
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0030.037
Open science0.0000.000
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 head0.150
GPT teacher head0.393
Teacher spread0.243 · 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

Citations3
Published2021
Admission routes3
Has abstractyes

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