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Record W3126436188 · doi:10.29173/iasl7586

Teacher Librarians a Tour de Force for Information Literacy in Hong Kong Schools

2021· article· en· W3126436188 on OpenAlexvenueno aff
James Henri, Wah-Hing Betty Chu

Bibliographic record

VenueIASL Annual Conference Proceedings · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumInformation literacyFace (sociological concept)Principal (computer security)SociologyPedagogyLiteracyTeacher educationPolitical scienceLibrary scienceMedical educationMathematics educationPsychologyMedicineComputer science

Abstract

fetched live from OpenAlex

The process of curriculum reform in Hong Kong schools has been an ongoing process since 1998. This reform has been largely driven by the catch phrase ‘learning to learn’ and has demanded a more student centered curriculum and pedagogy. Essential ingredients in this reform have been the demand for better qualified teachers, for IT savvy teachers, and for teachers and students who are able to effectively use information to solve problems. Perhaps not surprisingly, the teacher librarian and information services to schools were identified as key ingredients in the change process. Indeed, whereas a decade ago very few schools were equipped with a central library, today almost all schools have one. Likewise a decade ago few schools employed a teacher librarian where as today the post of teacher librarian is one of only two mandated positions in schools; the other being the principal. In addition, all newly appointed teacher librarians are required to complete a two year part time Diploma in Teacher Librarianship that is paid for by the employing authority (although participating teacher librarians face a modest course fee). Participating teachers are allocated time release to support their participation in the program.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.376
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0020.062
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.293
Teacher spread0.275 · 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; both teacher heads agree on what is shown here.

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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