Epistemologies of Domination: Colonial Encounters, Heterology, and Postcolonial Pedagogy
Bibliographic record
Abstract
Abstract This article theorizes and establishes some of the outlines of an epistemology of domination. An epistemology of domination interpellates the question of “how/what does the oppressor know about the oppressed?” Drawing on several studies of cultural encounters such as Ibrahim Abu-Lughod's The Arab Rediscovery of Europe, Ashis Nandy's The Intimate Enemy, and Zeynep Çelik's Europe Knows Nothing about the Orient, the discussion explores epistemic tropes around colonial encounters: the power and politics of representation; the burden of belatedness/the denial of coevalness; the over-emphasizing of Western agency. Wlad Godzich states that “Western Thought has always thematized the other as a threat to be reduced, as a potential same-to-be, a yet-not-same.” My discussion here accepts this premise but only partially, and asks the question: does domination always entail the projection of alterity as a threat, or is there a wider spectrum of epistemic projections? How does the other encounter and experience the Western self, and does such encounter modify hegemonic epistemological paradigms? Following Michel de Certeau's assertion that “what is near masks a foreignness,” I seek to complicate the relation between selfhood and otherness in the colonial encounter, and its entanglements with colonial violence. What pedagogical moments emerge from such encounters? And how do such pedagogical moments structure postcolonial epistemologies?
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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 | 0.011 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.016 | 0.153 |
| Scholarly communication | 0.016 | 0.013 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.003 | 0.007 |
| 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".