Bibliographic record
Abstract
Libraries have benefitted from the extraction of Indigenous Knowledges and cultural materials through which they have sought to complete collections. This has led Indigenous communities to distrust of research and research institutions, recognizing the deep harms and exploitation of these research practices. This article undertakes a case study of the book The Sacred Scrolls of the Southern Ojibway to reveal the ways in which extractive research, publishing, and collections practices are known to Indigenous communities and are refused by them. This discussion pursues the publication and collections history of this book through the framework of refusal, an Indigenous feminist practice that asserts Indigenous Sovereignty and care practices over Knowledge. Refusal should be viewed as a generative space (Tuck and Yang 2014a) and should be taken as an invitation for libraries to question and critically evaluate the very foundational principles of our profession and practices. This article challenges three deeply held library assumptions that are revealed through refusal: (1) that extraction is inevitable, (2) that the library is the only appropriate place to steward materials, and (3) that communities should be invested in the future of the library. The call to reconceptualize extraction through refusal is essential: libraries that do not strive to be reciprocal and transformational in their relationships with Indigenous peoples will only serve as a barrier to Indigenous resurgence. Instead, we must reconceptualize librarianship practices toward a liberatory 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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.026 |
| Scholarly communication | 0.017 | 0.018 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.063 | 0.035 |
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".