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Record W3151683511 · doi:10.29173/iasl7940

Sparking a Worldwide Conversation on School Libraries 2.0

2021· article· en· W3151683511 on OpenAlexaffvenue
Marlene Asselin, Ray Doiron

Bibliographic record

VenueIASL Annual Conference Proceedings · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsUniversity of Prince Edward IslandUniversity of British Columbia
Fundersnot available
KeywordsConversationSPARK (programming language)Resource (disambiguation)Key (lock)Process (computing)Set (abstract data type)Computer scienceWorld Wide WebPublic relationsSociologyPolitical science

Abstract

fetched live from OpenAlex

The guest co-editors of the School Libraries Worldwide special topic issue on New Learners, New Literacies and New Libraries provide a summary of the key goals of the issue and the worldwide conversation they hope to spark by sharing a diverse set of articles and online resources. Details are provided on developing the journal issue as an open source, online resource; the call for proposals; and the subsequent review process for the issue. The editors provide a further synthesis of key points suggested throughout the review process and the subsequent “publication” of the issue. Questions are raised about reluctance from the field to accept the notion of new learners and new literacies and a tactic claim that these issues are already being addressed in school libraries. The challenge is given for the readers/viewers of this special issue to get engaged in the conversation by responding at the SLW Blog.

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)0.061
metaresearch head score (Gemma)0.078
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: Other · Consensus signal: none
Teacher disagreement score0.950
Threshold uncertainty score0.323

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0610.078
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.003
Science and technology studies0.0140.013
Scholarly communication0.0500.038
Open science0.0020.025
Research integrity0.0220.026
Insufficient payload (model declined to judge)0.0180.006

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 head0.027
GPT teacher head0.275
Teacher spread0.248 · 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
GenreOther

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".

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Citations1
Published2021
Admission routes2
Has abstractyes

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