Race and Pedagogical Practices: When Race Takes Center Stage in Philosophy
Bibliographic record
Abstract
This paper presents a segment of a broader research project titled “When Black Consciousness Meets White Consciousness,” which first developed out of my research work with White women in violence‐against‐women organizations. It documents an interview between a White woman and me, a Black South African philosopher. I lived and worked in Canada at the time but I traveled to the United States for conferences on a regular basis. I was presenting my work on Black consciousness, White consciousness, and Black existentialism—relying on Derridean deconstruction and psychoanalysis—when I had the exchange with a White woman, a young faculty member in the philosophy department, which had jointly hosted the talk with the women and gender studies department. This paper offers a verbatim account of this dialogue wherein the history of philosophy is unraveled and where I draw on Jacques Derrida's “White Mythology” to demonstrate how White consciousness is engraved. It is out of this intertwined analysis that my work on White consciousness emerged in the 1990s—and with which I continue—as is evidenced throughout the paper. In unpacking this dialogue, I situate the complexities that arise from the pedagogical practices within philosophy when race takes center stage within a discipline that has written itself as though race does not exist.
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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 | 0.020 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.019 | 0.088 |
| Scholarly communication | 0.015 | 0.020 |
| Open science | 0.001 | 0.016 |
| Research integrity | 0.003 | 0.011 |
| Insufficient payload (model declined to judge) | 0.002 | 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".