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Record W2187649642 · doi:10.29173/iasl7655

Information Literacy Practices in Brazilian School Libraries

2021· article· en· W2187649642 on OpenAlexvenueno aff
Bernadete dos Santos Campello

Bibliographic record

VenueIASL Annual Conference Proceedings · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Digital Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsInformation literacyLiteracySociologySchool libraryPedagogySample (material)Public relationsPsychologyMedical educationPolitical scienceLibrary scienceComputer scienceMedicine

Abstract

fetched live from OpenAlex

Based on the assumption that collaboration of librarians with teachers is central to the concept of information literacy, this study aims to understand the vision of the librarian with regard to collaboration, if he/she realizes the difficulties in this collaboration and in what way he/she seeks to collaborate. A qualitative/interpretative methodology was used and data were collected through reports of experiences, interviews and group discussion. The sample was composed of 28 school librarians (14 from public schools and 14 from private institutions). Results show that librarians not only understand the need for collaboration with teachers for the success of their educational practice, but also engage themselves in concrete actions to achieve that collaboration, which reveals a pro-active attitude, different from the projected image of a professional isolated from school life. This attitude indicates that Brazilian school librarians are starting to build the foundations for their educational practice, which could pave the way for the establishment of information literacy programs in Brazilian schools.

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)0.004
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.005
Science and technology studies0.0070.003
Scholarly communication0.0060.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.040
GPT teacher head0.352
Teacher spread0.313 · 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 designObservational
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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