“What if technology worked in harmony with nature?” Imagining climate change through Prius advertisements
Bibliographic record
Abstract
In this article we examine the marketing representations of the Toyota Prius, the first ‘green’ mass-produced automobile. Drawing on an interpretive analysis of Prius print advertisements in Canadian publications between 2006–2011 and a matched sample of other automobile advertisements, we observe how the Prius advertisements invoke imagination and how this process is channelled, via the integration of text and images offered in the advertising space, to particular themes and ideas. Through the use of an ambiguous system of signs, audiences are invited to imagine and thereby co-create the significance of hybrid electric vehicles. Three areas of imagining are emphasized by the advertisement structure—nature, harmony and agency—and we analyze these imaginings as potential moments of knowledge creation about climate change. We examine how the activity of imagining in relation to these three areas influences viewers’ knowledge and perception of climate change as well as their sense of responsibility for anthropogenic climate change. We discuss the consequences of using ambiguous messages to promote socially and politically charged products for consumers’ understanding and imagination.
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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 | 0.001 |
| Science and technology studies | 0.004 | 0.024 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".