(Not so) crude text and images: staging<i>Native</i>in ‘big oil’ advertising
Bibliographic record
Abstract
Transnational energy companies' representations of Indigenous bodies and landscape in corporate advertising and social responsibility reporting can be thought of as staged and operating on more than one level of meaning. Understanding these representations as performative makes clear these are ongoing social and cultural constructs embedded in a body of discourse that is marked by White culture's own desire for permanence and fixity in relation to a privileged positioning. The staging of Native bodies and landscapes, in part intended to allay growing public concerns about environmental impacts associated with fossil fuel production, is achieved through the strategic use of images and text. Semiological analysis helps to make explicit the manner in which oil and gas transnationals' displaying of a racialised Native subject in the context of ‘partnership’ serves as a greenwashing strategy consistent with Canada's own dominant national narratives. Recognising advertisements and corporate social responsibility reports not as neutral knowledge but as sites of knowledge production reveals myths and stereotypes that serve to prevent, rather than encourage, true sustainability.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".