MétaCan
Menu
Back to cohort
Record W3144422736 · doi:10.29173/iasl7447

School Library Research Rocks

2021· article· en· W3144422736 on OpenAlexaffvenue
Gooneshwaree Beesoon, Jennifer Branch-Mueller

Bibliographic record

VenueIASL Annual Conference Proceedings · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSchool libraryLibrary scienceInformation literacyProfessional developmentSociologySchool teachersMedical educationLiteracyPedagogyPolitical sciencePsychologyMedicineComputer science

Abstract

fetched live from OpenAlex


 
 
 This research examined the state-of-the-art of research in school librarianship. Similar trends from previous research were confirmed: research in school librarianship is published in two major journals -- School Library (Media) Research and School Libraries Worldwide. Almost 80% of the research was carried out in the United States. There is a small core group of researchers working in the area of school librarianship. About half of all research is by a single author. The main themes from the research included collaboration between teachers and school librarian, technology integration, the instructional role of school librarians, professional development, analysis of materials, information literacy instruction, practices and assessment, hiring, professional development and retention of school librarians, use of multimedia resources, role of school librarians in the provision of health information, motivation of students, and research in other parts of the world.
 Frameworks (Aharony, 2011; Koufogiannakis, Slater & Crumley, 2005; Mardis, 2011) were incomplete and the authors present a new framework for categorizing school library research, in particular, but also LIS research, in general.
 
 

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Other
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptno category
Domain: not available · Genre: Other
About the Canadian research system: no · About a Canadian topic: no
Other designlow
models splitAgreement compares identical category sets and study designs across arms.

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, Insufficient payload (model declined to judge)
Consensus categoriesScholarly communication, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.478
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
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0020.032
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.066
GPT teacher head0.360
Teacher spread0.294 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designNot applicable · Other design
Domainnot available
GenreOther

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

Citations3
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueIASL Annual Conference ProceedingsSame topicLibrary Science and Information LiteracyFrench-language works237,207