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Record W2187460848 · doi:10.29173/iasl8080

Developing 21st Century School Media Resource Libraries for Singapore

2021· article· en· W2187460848 on OpenAlexvenueno aff
Shaheen Majid, Abdus Sattar Chaudhry, Schubert Foo, Elisabeth Logan

Bibliographic record

VenueIASL Annual Conference Proceedings · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsnot available
Fundersnot available
KeywordsResource (disambiguation)School libraryFocus groupSupervisorPublic relationsSchool teachersSociologyLibrary sciencePolitical scienceMedical educationPedagogyMedicineComputer science

Abstract

fetched live from OpenAlex

In light of global calls for emphasizing innovative thinking and creative problem solving in elementary and secondary schools and a more collaborative role for school media resource libraries to support the new focus, a taskforce of four faculty members from the Division of Information Studies of Nanyang Technological University undertook to assess the status of a selected group of thirteen media resource libraries in Singapore. Data obtained from questionnaires and focus groups indicate that for Singapore's School Media Resource Libraries to play a significant role in supporting the new educational focus some important changes are needed. Recommendations from the taskforce include a change in status of the School Media Resource Library and its supervisor, additional training and education for these supervisors, improved access and connectivity for inter-school cooperation, and more collaborative collection management policies.

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)0.018
metaresearch head score (Gemma)0.013
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 score0.018
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.003
Science and technology studies0.0040.001
Scholarly communication0.0150.011
Open science0.0030.009
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0120.003

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 head0.041
GPT teacher head0.288
Teacher spread0.247 · 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".

Quick stats

Citations5
Published2021
Admission routes1
Has abstractyes

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