Cross-Cultural Museum Bias: Undoing Legacies of Whiteness in Art Histories
Bibliographic record
Abstract
Abstract When museums are used as sites of knowledge production and research, what are their responsibilities for anti-racist public education? Examining the racial logics that govern, organize, and fund museums, this essay focuses on institutional bias within knowledge production and argues that locating racial logics within museums can be an act of radical pedagogy. Museums are being challenged to become sites of social change, making it vital to study their power structures and the ways in which they organize and study other cultures, illuminating imperial and colonial biases existing at their foundations. The Canadian Museum of Civilization’s exhibition The Lands within Me: Expressions by Canadian Artists of Arab Origin , is a relevant case study as it opened within weeks of September 11, 2001. The moral panic surrounding the show provides a powerful glimpse of the ways in which certain narratives are excluded from Canadian national projects and how these racial projects exist within museums. Works by Camille Zakharia, an artist included in the exhibition, will be analyzed and the fragmented forms of his photo collages will be used as an organizing metaphor to discuss Canadian multiculturalism, racialization, and citizenship.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".