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Record W3134933609 · doi:10.29173/iasl7909

Possibilities for implementation of information literacy programs in Brazilian school libraries

2021· article· en· W3134933609 on OpenAlexvenueno aff
Bernadete dos Santos Campello

Bibliographic record

VenueIASL Annual Conference Proceedings · 2021
Typearticle
Languageen
FieldComputer Science
TopicInformation Science and Libraries
Canadian institutionsnot available
Fundersnot available
KeywordsInformation literacyVariety (cybernetics)Context (archaeology)Perspective (graphical)LiteracyComputer sciencePolitical scienceMathematics educationSociologyPedagogyLibrary sciencePsychologyGeography

Abstract

fetched live from OpenAlex

An analysis was made of the Brazilian National Curricular Standards for basic education in order to identify skills related to information literacy, using AASL Information Power as basis. The objective of this analysis was to investigate the extent to which these skills are represented in the Brazilian educational policy document and if they are viewed as integral part of students’ comprehensive literacy. The analysis showed that NCS include the basic information literacy skills (to access, evaluate and use information). Emphasis on independent learning by means of a variety of information resources is present in the document as well as issues regarding social responsibility. So, there is a positive perspective for information literacy programs to be developed in Brazilian schools in the context of the official curricular guidelines.

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)0.012
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.025
GPT teacher head0.289
Teacher spread0.264 · 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.

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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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