Counterclaims: Examining and contesting white entitlement to the space of the university through the labour of anti‐racist student organizers
Bibliographic record
Abstract
This paper examines competing spatial claims to one urban Canadian university through a case study conducted with 11 anti‐racist student organizers. Situated in literatures which critically examine whiteness in the university, this study illustrates how active producers of whiteness claim space in the university and how in turn, student organizers counter these claims through their anti‐racist labour. This case study explores the psychic geographies of the university by focusing on the affects which justify and motivate these spatial claims. First, I consider how distorted fears of racial justice both reproduce and justify whiteness and are then articulated through stereotyping, surveillance, and stalling. I then illustrate how anti‐racist student organizers stake counterclaims to the space of the university through their labour, motivated by hope and routed through the “underground” or “undercommons” of the university. Ultimately, this case study seeks to demystify and challenge the distorted and racist fears and subsequent actions of white actors specifically, in order to undo the affects through which whiteness is spatially reproduced in the university.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.043 | 0.054 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".