The eyes of the world are upon us : the role of visual images in the fight over Alberta's oil sands
Bibliographic record
Abstract
In the controversy over the mining of the Alberta oil sands, tourism has become a tool used by both those who want to stop further development of the oil sands and perhaps also by those who want it to continue. The goal of this research is to examine how the visual images of the environment, within the context of tourism, are being used to influence public opinion over the oil sands operations. Through a multistep process, promotional materials from tourism brochures, guidebooks, and websites, and also from anti-oil sands campaign websites, were analyzed according to their content, with just under 2000 images examined. Nature-tourism is the dominant form of tourism in the oil sands region, and therefore tourism experiences and images from the oil sands region largely feature images of wildlife, scenic views, and outdoor activities in the oil sands region. In contrast, images used by the Rethink Alberta campaign and other anti-oil sands organizations focus on mining operations themselves and their immediate negative effects on the environment. Results of the examination found differences in means of distribution, environmental emphasis, and geographical scale between material from tourism and from anti-oil sands campaigns. The differing goals of the tourism industry and the anti-oil sands campaigns were also reflected in the imagery used, with tourism attempting to attract visitors to pristine environments, while anti-oil sands groups are trying to discourage visitation as a form of protest. By promoting the availability of outdoor experiences through advertisements for nature-tourism activities, and wide use of visual images featuring aspects of nature, the tourism industry may be unintentionally countering anti-oil sands campaign groups’ allegations of wanton ecological destruction and unsustainability.
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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 | 0.006 | 0.007 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".