From object to objectified: The ongoing precarity of Black bodies in institutional spaces
Bibliographic record
Abstract
This article examines the precarity of Black bodies in institutional spaces, particularly the detrimental impact on the career of the Black arts practitioner. Ongoing systemic discrimination within institutional sites, as experienced by Black artists, scholars and curators, can be traced to the problematic historical relationship of the Black body to the exhibitionary complex. The continued performative spectacularization of Blackness in institutional settings, as in the cases of Artists Space in 1979 and the Nova Scotia College of Art and Design in 2021, highlights the difficulty for Black professionals invested in decolonial work to unsettle this misrepresentation without the risk of repercussions. In each case study, institutional responses to claims of racial discrimination illuminate their negation of the Black experience and the consequence to Black practitioners of questioning and activating against systemic inequities within these sites. To address the topic in an honest and scholarly manner, this article includes references to histories of colonial violence, as well as examples of harmful racial slurs exacted in response to the concerns of Black practitioners. In so doing, this article is an act of decentring imperialist research methods’ and engages an alternative method for exploring deeply sensitive narratives in a rigid institutional structure.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.027 | 0.089 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.001 | 0.017 |
| Research integrity | 0.003 | 0.006 |
| 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".