Bibliographic record
Abstract
This article explores how artists, by adopting the posture of an artist-museologist, can propose new understandings between museums, their collections, broader perceptions of knowledge, and the power of choosing what constitutes the museum through a critical-historical account of the Royal Tyrrell Museum’s historical and ongoing relationship to resource extraction and Indigenous land dispossession. We define the term artist-as-museologist as an artist who is concerned with borrowing, addressing, infiltrating, or operating through museum collections, their scenography, or dissemination activities. Applying institutional critique to the museum, we show how artistic practice can help to excavate buried power relations that condition the extractive museum, like the Royal Tyrrell, named after geologist, Joseph Burr Tyrrell, who discovered the Albertasaurus during an expedition of the Geological Survey of Canada. The artist, we argue, has the potential to do such excavation by surfacing stories and relations that have slipped between cracks or have been written out altogether. We look specifically at Bigras-Burrogano’s current projects that explore the tensions between the Canadian settler-colonial state’s use of natural imagery to constitute national identity and its extractivist economy. By providing a critical history of the Royal Tyrrell Museum’s imbrication with extractive enterprise and the settler-colonial state while reflecting on two art pieces that directly respond to these conditions, this article ultimately proposes that the artist-as-museologist has an integral role to play in creating conditions for non-extractive museological and curatorial practices.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.147 | 0.045 |
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".