Critical Information Literacy Teaching in British Columbia Academic Libraries
Bibliographic record
Abstract
This paper provides an overview of research and findings related to the application of critical information literacy (CIL) theory in B.C., Canada, higher education library practices. A gap was identified in the literature related to information literacy teaching in Canada, leading to the question: How are librarians in B.C. higher education applying critical information literacy in their practice? A mixed methods research study was conducted with higher education librarians, through a survey of all public higher education libraries and subsequent semi-structured interviews. Findings include librarian awareness of critical information literacy and the ACRL Framework for information Literacy, but a gap in practical application. Indigenization, a form of de-colonizing library practices, is one area of common focus for B.C. higher education librarians in applying a critical lens to library practices. The research also identified areas where further support is required and recommendations for improving the application of theory in practice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.020 | 0.006 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".