Exhibiting the Extractive: Bitumen in Fort McMurray
Bibliographic record
Abstract
This article explores how bitumen is curated by the Fort McMurray Oil Sands Discovery Centre and, by extension Suncor’s recent, but no longer operational, ‘Experience the Energy’ tour. In doing so, I seek to examine the visual culture of bitumen as produced from the perspective of industry. The Fort McMurray Oil Sands Discovery Centre is a provincially-funded, industry-sponsored facility operated jointly by Alberta Culture and Tourism and the province’s Historic Sites and Museum Branch. The Centre’s central focus is education and, to enhance this focus, it incorporates entertainment and interactive exhibitions with bitumen throughout, which help to communicate its representation of the histories of the tar sands. I present Suncor’s ‘Experience the Energy’ tour as an extension of the curatorial practices at the Oil Sands Discovery Centre. To do so, I recount my own experience with tar sands tourism in Fort McMurray, framing Suncor’s industrial tourism as a curation of the physical experience of extractive sites, while connecting this to the visual tactics employed at the Centre. In the article, I emphasize how an established visual language, rooted in settler-colonial and extractive-capitalist practices, is adapted to maintain and advance the industrial operations and development of the tar sands. To better understand how visitors come to know bitumen and extraction in these spaces, I consider the sensory as a key component of visual culture to explore how the tar sands industry calls upon visual culture to advance its cause, and suggest that both the tour and the Centre are a kind of multisensory curatorial project—one based on bitumen.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".