Glued to the Image: A Critical Phenomenology of Racialization through Works of Art
Bibliographic record
Abstract
I develop a phenomenological account of racialized encounters with works of art and film, wherein the racialized viewer feels cast as perpetually past, coming “too late” to intervene in the meaning of her own representation. This points to the distinctive role that the colonial past plays in mediating and constructing our self‐images. I draw on my experience of three exhibitions that take Muslims and/or Arabs as their subject matter and that ostensibly try to interrupt or subvert racialization while reproducing some of its tropes. My examples are the Jean‐Joseph Benjamin‐Constant exhibition at the Montreal Museum of Fine Arts (2015), the exposition Welten der Muslime at the Ethnologisches Museum in Berlin (2011–2017), and a sculpture by Bob and Roberta Smith at the Leeds City Art Gallery, created in response to the imperial power painting, General Gordon's Last Stand, that is housed there. My interest is in how artworks contribute to the experience of being racialized in ways that not only amplify the circulation of images but also constitute difficult temporal relations to images. Drawing on Frantz Fanon's Black Skin, White Masks, I argue that such racialized images are temporally gluey, or stuck, so that we are weighted and bogged down by them.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.026 | 0.087 |
| Scholarly communication | 0.015 | 0.015 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.005 | 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".