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Record W2952913917 · doi:10.29173/slw8217

Possibilities of Modern School Libraries in Pesantren in Indonesia: A Case Study with Two Young Muslim Women

2021· article· en· W2952913917 on OpenAlexvenueno aff
Yuriko Nakamura

Bibliographic record

VenueSchool Libraries Worldwide · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Character Development
Canadian institutionsnot available
FundersJapan Society for the Promotion of Science
KeywordsIndonesianApprenticeshipOpenness to experienceIslamSchool librarySociologyBoarding schoolTRIPS architectureMathematics educationPedagogyLibrary sciencePsychologyEngineeringGeographyComputer scienceSocial psychology

Abstract

fetched live from OpenAlex

In this case study, the potential for modernizing school libraries in pesantren, Indonesian Islamic boarding schools, is explored. n, a Japanese Library Science researcher, met and interacted with two Indonesian Muslim women, a student and an apprentice teacher from two different pesantren in Java. Guided by the author, the student and apprentice were introduced to modern libraries through trips to Jakarta and Tokyo in 2012. By observing and analyzing the two participants’ words and conduct, as well as the photos and notes they took, the author found that they showed a distinct interest in introducing new types of activities to their own school libraries. In particular, both participants noted their approval of the student research projects displayed in the Japanese school libraries they visited; this positive reaction suggests the Indonesian participants’ openness to new styles of teaching and learning.

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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.003
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.017
GPT teacher head0.279
Teacher spread0.262 · 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 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

Citations0
Published2021
Admission routes1
Has abstractyes

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