Bibliographic record
Abstract
This conceptual research examines epistemic injustices in library and information science (LIS) due to the power imbalance between Western and non-Western LIS curricula, theory, and practice. It is equally critical to consider the presence of epistemic injustices in adjacent LIS domains (e.g., classification, preservation, digital scholarship); for if we work to prioritize access or digitize materials without considering historical oppression, we are at risk of perpetuating these same injustices. In this work, we utilize the concept of epistemic harm to understand the international dimension of epistemic injustice. This paper introduces the concept of critical international librarianship, which we define as recognizing, examining, critiquing, and subverting the power structures and hegemonies in library and information systems that exist among two or more nations in practice, pedagogy, and research. Critical international librarianship serves as an intervention for epistemic injustices. It provides a direction for the practitioners and researchers who pursue critical international librarianship to move toward a long-overdue epistemic justice in international LIS.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.052 |
| Scholarly communication | 0.015 | 0.023 |
| Open science | 0.001 | 0.015 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".