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Record W3135179369 · doi:10.29173/iasl7474

Growing from Nothing

2021· article· en· W3135179369 on OpenAlexvenueno aff
Joyce Chen, Li-jen Tseng

Bibliographic record

VenueIASL Annual Conference Proceedings · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Administration
Canadian institutionsnot available
Fundersnot available
KeywordsReading (process)Christian ministryCronbach's alphaPsychologyMathematics educationPedagogyMedical educationSchool libraryLibrary sciencePolitical scienceMedicineComputer science

Abstract

fetched live from OpenAlex


 
 
 Since 2009, Taiwan's Ministry of Education has begun to add the post of teacher librarians in some elementary schools. Teachers who are enthusiastic about reading education become teacher librarians to take charge of managing school libraries and promoting reading after receiving short professional training. This study aims to probe into whether the system is helpful to the management of libraries in elementary schools and to the establishment of reading environment at school.
 Specifically speaking, this study aims to discuss whether there is any difference in the activities of school libraries and schools' attitudes toward reading between schools with teacher librarians and schools without ones. The study surveyed elementary schools in Taiwan with a questionnaire which was filled out by teacher librarians or general librarians at school. The questionnaire was tested with Cronbach’s α reliability, and a coefficient of 0.975 was obtained, which is considered excellent reliability.
 742 copies of the questionnaire were retrieved, and 741 of them were considered valid after the elimination of one with incomplete answers. Among which, 213 copies were from schools with teacher librarians, and the rest 528 copies were from schools without teacher librarians. In addition, the fill rate of schools with teacher librarians reached 80%. The study found that schools with and without teacher librarians had significant differences in library management of their libraries and behavior and attitudes toward reading.
 
 

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.185
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.005
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.040
GPT teacher head0.298
Teacher spread0.258 · 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 teacher head, 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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