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Record W327955559 · doi:10.29173/cais369

Integrating Information Behaviour and Information Literacy During Academic Tasks: A Comparative Study of Japanese and Canadian Undergraduate Students in Canadian Universities

2013· article· fr· W327955559 on OpenAlexaffvenueabout
Yusuke Ishimura, Joan C. Bartlett

Bibliographic record

VenueProceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI · 2013
Typearticle
Languagefr
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsMcGill University
Fundersnot available
KeywordsInformation literacyHumanitiesLibrary sciencePsychologySociologyPedagogyArt

Abstract

fetched live from OpenAlex

This presentation reports preliminary results from doctoral research that investigates the information behaviour and information literacy skills of Japanese and Canadian undergraduate students during their research tasks in Canadian universities. Differences and similarities in behaviours and skills between the two groups are identified through analysis of research portfolios and interviews.Cette communication présente les résultats préliminaires d'une étude doctorale portant sur le comportement informationnel et la maîtrise de l'information des étudiants japonais et canadiens de premier cycle lors de leurs travaux de recherche dans les universités canadiennes. Les différences et les similitudes dans les comportements et les habiletés des deux groupes sont décelées au moyen de l'analyse des dossiers de recherche et d'entrevues.

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)0.009
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 score0.061
Threshold uncertainty score0.138

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.007
Science and technology studies0.0090.003
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.271
Teacher spread0.257 · 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
Published2013
Admission routes3
Has abstractyes

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Same venueProceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSISame topicLibrary Science and Information LiteracyFrench-language works237,207