Shifting Established Mindsets and Praxis in Libraries: Five Insights for Making Non-Western Knowledge Digitally Accessible through Community Engagement
Bibliographic record
Abstract
This paper is a reflection on the challenges encountered and decisions made as part of a multi-year community-based action research project to digitally curate a living oral tradition. At the core of this initiative was an exploration of the ways academic librarians in Canada can leverage existing library services and systems and engage with the community to improve accessibility of non-Western knowledge materials. The author collaborated with several members of the Ismaili community across western Canada to find ways to digitally curate their revered oral tradition of ginans (gnostic and devotional hymns) in a culturally respectful and responsible way. The purpose of this article is to share five insights gained during the course of this exploration: 1) value relationships over tasks; 2) accept community engagement as a continuum; 3) learn to appreciate rather than appropriate materials; 4) consider oral sources to be as important as textual ones; and 5) accept community materials as credible knowledge resources.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.018 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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; both teacher heads agree on what is shown here.
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".