Transformations of Oil: Visibility, Scale, and Climate in Warren Cariou’s Petrography
Bibliographic record
Abstract
Dans cet article, j’examine la série Petrography (2014 au présent), dans laquelle Warren Cariou commente sur les perceptions et représentations de l’énergie pétrolière. Utilisant une technique inspirée de Nicéphore Niépce, l’artiste multidisciplinaire winnipegois met en évidence dans ces pétrographies (« petroleum-photography ») une question fondamentale de l’anthropocène : la division continuelle et problématique entre les relations humaines et non humaines, qui découle de la conception du non humain en tant que ressource passive. Mon analyse de cette série met en lumière la façon dont les pétrographies de Cariou réutilisent une ressource naturelle pour attirer notre attention sur notre dépendance au pétrole et la contradiction qui en résulte à cette ère de changement climatique.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".