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Record W2772826681 · doi:10.11645/11.2.2219

Celebrating Undergraduate Students’ Research at York University

2017· article· en· W2772826681 on OpenAlex
Sophie Bury, Dana Craig, Sarah Shujah

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

VenueJournal of Information Literacy · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsCentennial CollegeYork University
Fundersnot available
KeywordsInformation literacyUndergraduate researchHigher educationSociologyOrder (exchange)Mathematics educationLibrary sciencePsychologyMedical educationPedagogyPolitical scienceMedicineComputer science

Abstract

fetched live from OpenAlex

This article analyses the information literacy (IL) competencies of high-achieving undergraduate students through the lens of undergraduate research celebrations in a North American University. This article focuses on York University’s Undergraduate Research Fair, and shares findings from an analysis of students’ IL award submissions including lower-year (first and second year of university) and upper-year (third and fourth year of university) applicants. Submissions are analysed using a qualitative content analysis approach. The study’s findings point to the positive value of both IL and reference help in building high-achieving undergraduate students’ IL skills. Results indicate important future directions for IL instruction, such as the role of the flipped classroom, and the critical importance of embracing the Association of College and Research Libraries’ (ACRL) Framework for Information Literacy for Higher Education to engage undergraduates with high-order IL concepts.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.818
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.000
Scholarly communication0.0030.076
Open science0.0010.000
Research integrity0.0000.000
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 head0.052
GPT teacher head0.396
Teacher spread0.344 · 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