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Record W2980316447 · doi:10.29173/iasl7226

Acquired but not Required?: the Gap between the Competency in Education and That in Action for School Librarianship

2016· article· en· W2980316447 on OpenAlexvenueno aff
Takuma Nakamura, Fumie Niwai, Mitsuhiro Oda, Yutaka Mabe

Bibliographic record

VenueIASL Annual Conference Proceedings · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsnot available
Fundersnot available
KeywordsAction (physics)Work (physics)PedagogyMedical educationPsychologyEngineeringMedicine

Abstract

fetched live from OpenAlex

This study confirms the gap between the competency of “school librarian” in education and that in action. The authors carried out the semi-structured interviews with eight persons who had experience of working as a school librarian. The authors asked them whether they thought that it was necessary to learn the competency in the list made by authors, and whether they utilized that at their works. As a result, most of the competencies was required at work, moreover, it was necessary to learn in education. According to their answers, the authors recognized following things. Firstly, there was little need to learn some competencies in the categories of library management and organization of materials. Secondly, the competencies about history, other types of library and school librarianship of foreign countries should be learned in education, though those were not utilized at work. Thirdly, the competency of pedagogy should be added to the list.

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)0.015
metaresearch head score (Gemma)0.040
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 score0.015
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.040
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0030.008
Scholarly communication0.0060.011
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.089
GPT teacher head0.328
Teacher spread0.239 · 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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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