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Record W2993278287 · doi:10.11645/13.2.2578

Connecting theory to practice

2019· article· en· W2993278287 on OpenAlexaff
Kieren Bailey, Michele Jacobsen

Bibliographic record

VenueJournal of Information Literacy · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsUniversity of CalgaryNorthwestern Polytechnic
Fundersnot available
KeywordsJournaling file systemLibrary instructionSession (web analytics)Computer scienceInformation literacyCommunity of inquiryMathematics educationPedagogyPsychologyLibrary scienceWorld Wide WebComputer file

Abstract

fetched live from OpenAlex

This design-based research study of library instruction was developed using the Community of Inquiry theoretical framework. Three different instructional approaches were developed and evaluated as part of this study: the one-shot session approach, the partially embedded librarian approach and the fully embedded librarian approach. Surveys, interviews and journaling were used to gather data from faculty, undergraduate students and the researcher–librarian about their experiences. This research study is unique given the combined use of design-based research methodology and the Community of Inquiry theoretical framework to collaboratively design and evaluate library instruction.

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)0.044
metaresearch head score (Gemma)0.060
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.044
Threshold uncertainty score0.232

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0440.060
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.005
Science and technology studies0.0050.028
Scholarly communication0.0200.014
Open science0.0050.010
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0090.002

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 head0.006
GPT teacher head0.312
Teacher spread0.306 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations2
Published2019
Admission routes1
Has abstractyes

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