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Record W3142675243 · doi:10.29173/iasl7797

Other Ways of Knowing: How School Librarians Can Take a Leadership Role in Addressing Multi-literacies Across the Curriculum in the School Library

2021· article· en· W3142675243 on OpenAlexvenueno aff
Meghan Harper

Bibliographic record

VenueIASL Annual Conference Proceedings · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumPresentation (obstetrics)Reading (process)LiteracyInformation literacyPedagogySchool librarySociologyMathematics educationPsychologyPolitical scienceComputer scienceLibrary science

Abstract

fetched live from OpenAlex

School librarians have a unique, unprecedented, and unparalleled opportunity to affirm their role in students’ use of basic literacy skills – reading and writing – while highlighting their relatively new role, guiding students through the acquisition of information through multiple modes of communication with new technologies. School librarians can create and facilitate opportunities for students to enhance their learning and become multiliterate. These learning opportunities and a focus on “core” literacies shed a much needed spotlight on the important role and influence of the school librarian on overall academic achievement and the acquisition of multiliteracy skills that have become a necessity in a changing technological and global environment. This article isbased on a presentation given at the International Association of School Librarians Conference in Doha, Qatar (2012), the goals of which were to share an overview of the multiliteracies concept, suggest strategies for facilitating literacy in the school library and classroom, and share professional resources for continued learning and the integration of multiliteracies across the curriculum.

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 categoriesScholarly communication
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.161
Threshold uncertainty score0.998

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 studies0.0010.001
Scholarly communication0.0030.023
Open science0.0010.000
Research integrity0.0000.001
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 head0.115
GPT teacher head0.310
Teacher spread0.196 · 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 designQualitative
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

Citations1
Published2021
Admission routes1
Has abstractyes

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