MétaCan
Menu
Back to cohort

Advancing the Promotion of Information Literacy Through Peer-led Learning

2009· article· en· W2153453210 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCommunications in Information Literacy · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsInformation literacySession (web analytics)MentorshipCurriculumPromotion (chess)PedagogyLibrary instructionLiteracyMathematics educationCritical literacyPsychologySociologyComputer scienceMedical educationPolitical scienceMedicineWorld Wide WebPolitics

Abstract

fetched live from OpenAlex

Two new courses at the University of Windsor are opening the door to thinking about information literacy and curricular integration in very different ways. The courses, Ways of Knowing and Mentorship & Learning, were originally designed to help with retention and transition issues. They were also founded on the concept of peer-led learning at the university level. In this model students are able to connect with their peers in an organic way that is not always possible with faculty and librarians. It did not take long to see the potential in using peer mentors as potential conduits in the transfer of information literacy skills. This article tells the story behind the development of two courses and the mistakes that had to be made before the connection between mentors and information literacy could be seen. It also shows that by involving faculty and students in the design and delivery of an information literacy-integrated curriculum the library can accomplish far more than any one-shot, tool-based session.

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.

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)0.003
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.928
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.031
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.027
GPT teacher head0.432
Teacher spread0.405 · 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