At the Margins of Epistemology: Amplifying Alternative Ways of Knowing in Library and Information Science
Bibliographic record
Abstract
Abstract This panel argues a paradigm shift is needed in library and information science (LIS) to move the field toward information equity, inclusion, relevance, diversity, and justice. LIS has undermined knowledge systems falling outside of Western traditions. While the foundations of LIS are based on epistemological concerns, the field has neglected to treat people as epistemic agents who are embedded in cultures, social relations and identities, and knowledge systems that inform and shape their interactions with data, information, and knowledge as well as our perceptions of each other as knowers. To achieve this shift we examine epistemicide—the killing, silencing, annihilation, or devaluing of a knowledge system, epistemic injustice and a critique of the user‐centered paradigm. We present alternative epistemologies for LIS: critical consciousness, Black feminism, and design epistemology and discuss these in practice: community generated knowledges as sites of resistance and Indigenous data sovereignty and the “right to know”.
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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 | 0.054 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.015 | 0.152 |
| Scholarly communication | 0.031 | 0.040 |
| Open science | 0.003 | 0.030 |
| Research integrity | 0.006 | 0.009 |
| 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".