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Record W4401718437 · doi:10.21432/cjlt28776

Editorial

2024· editorial· en· W4401718437 on OpenAlexaffvenueabout
Martha Cleveland-Innes

Bibliographic record

VenueCanadian Journal of Learning and Technology · 2024
Typeeditorial
Languageen
FieldSocial Sciences
TopicEducational Tools and Methods
Canadian institutionsAthabasca University
Fundersnot available
KeywordsThe InternetEducational technologyLibrary scienceSociologyComputer scienceMathematics educationPedagogyWorld Wide WebPsychology

Abstract

fetched live from OpenAlex

Welcome to Volume 50, Issue 1, of The Canadian Journal of Learning and Technology (CJLT). CJLT is a decades-old peer-reviewed journal that invites English or French submissions on the research and practice of education, technology, and learning. This bilingual journal is free-of-charge to anyone with access to the Internet, is multi-indexed, and presented in accessible formats. There are no article submission/publication fees or access charges.

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)0.003
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.938
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.022
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.001
Science and technology studies0.0020.001
Scholarly communication0.0050.003
Open science0.0020.001
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.0620.045

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 head0.011
GPT teacher head0.348
Teacher spread0.337 · 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.

Study designNot applicable
Domainnot available
GenreEditorial

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
Published2024
Admission routes3
Has abstractyes

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