EPISTEMOLOGIES OF SITUATED KNOWLEDGES: “TROUBLING” KNOWLEDGE IN PHILOSOPHY OF EDUCATION
Bibliographic record
Abstract
Epistemologies of situated knowledges, advanced by scholars such as Donna Haraway, Lorraine Code, and Maureen Ford, challenge mainstream epistemology's claim to be the gold standard in determining what counts as knowledge. In this essay, James Lang uses the work of these and other feminist theorists to explicate the notion of situated knowledges and then uses this notion to trouble the legitimacy of employing Kantian‐inspired propositional rationalism to justify all knowledge claims. Lang challenges the notions of the discrete, objective, impartial, interchangeable subject and the static passivity of objects of knowing. He demonstrates the inevitable involvement of the subjective in knowledge construction and justification; he claims that knowledge is necessarily embodied, partial, and situated and, further, that its construction, claiming, and enacting are activities with moral and political ramifications. Finally, Lang shows that re‐visioning contexts of education through lenses of epistemologies of situated knowledges reveals a vastly expanded moral landscape with significant implications for educators, students, and educational theorists.
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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 | 0.017 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.013 | 0.134 |
| Scholarly communication | 0.014 | 0.031 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.008 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".