Where is Fort McMurray? The Camera as a Tool for Assembling "Community"
Bibliographic record
Abstract
In response to the global mythology spawned by visual representations of Fort McMurray, Canada, this article examines a critical, collaborative youth project that sought oblique entry points to prevailing storylines of “community” and to what it might mean to live in the shadow of one of the world’s largest resource extraction complexes. Building on visual methodologies where participants are encouraged to produce representations of home and place, we explore the two-way dynamic of the camera as a catalyst for assembling a temporary research collective and, by the same token, as a tool for composing and assaying the contours of “community.” The project under consideration encouraged participants to learn skills of photography and to dynamically engage with other participants, researchers, and the place(s) of Fort McMurray around the creation and public display of images in both on-line and off-line spaces. Where possibilities of “community” are polarized, occluded, and/or overdetermined by the visual narratives of rapid resource development, collaboration around the camera helps to discern and speak back to the fault lines of community — including as they play out in the everyday lives of youth. Specific photos and the narratives around them are used to illustrate how the camera created and revealed iterations and relations of community across multiple scales, from the microcosm of the photography research group to the regional infrastructure of oil sands production.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.024 | 0.019 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".