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Record W2969478887 · doi:10.29173/iasl7148

Nazarbayev Intellectual School Libraries: The Development of Functional Literacy and Reading Skills

2017· article· en· W2969478887 on OpenAlexvenueno aff
Aida Agadil, Olga Salamakhina, Gulmariyam Tubekbayeva

Bibliographic record

VenueIASL Annual Conference Proceedings · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsnot available
Fundersnot available
KeywordsReading (process)CreativityMulticulturalismRelevance (law)School libraryInformation literacyMathematics educationPedagogyLiteracyPsychologySociologyComputer scienceLibrary sciencePolitical science

Abstract

fetched live from OpenAlex

Nazarbayev Intellectual Schools (NIS) are a testing site for piloting innovations in teaching and learning in Kazakhstan’s formal education system. Fostering the development of multicultural, strong-minded students is a key component of an NIS school, and the library certainly plays an important role in the formation and development of students. This article presents the practical knowledge of NIS librarians which was gained through such practices as the use of applied gaming methods to promote reading, the development of information and functional literacy, the development of research skills and the development of functional literacy. School library activities should not have limitations; the school library is a center for reading, creativity and intellectual development. By using new methods, constantly improving and maintaining a friendly atmosphere, the school library will be able to maintain its relevance for students. Additionally, the school librarian will act as a guide for students as they explore the worlds of reading, imagination and academic achievements.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0000.000
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 head0.027
GPT teacher head0.290
Teacher spread0.263 · 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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