Satellite images as tools of visual diplomacy: NASA's ozone hole visualizations and the Montreal Protocol negotiations
Bibliographic record
Abstract
On 16 September 1987, the main chlorofluorocarbon-producing and -consuming countries signed the Montreal Protocol, despite the absence of a scientific consensus on the mechanisms of ozone depletion over Antarctica. We argue in this article that the rapid diffusion from late 1985 onwards of satellite images showing the Antarctic ozone hole played a significant role in this diplomatic outcome. Whereas negotiators claimed that they chose to deliberately ignore the Antarctic ozone hole during the negotiations since no theory was able yet to explain it, the images still loomed large for many of the actors involved. In Western countries, the National Aeronautics and Space Administration's (NASA) satellite visualizations were diffused through the general press and television stations. Other popular and mass media outlets followed quickly. In describing the circulation and appropriation processes of these images within and beyond the scientific and negotiation arenas, we show that the ozone hole images did play an important part in ozone diplomacy in the two years leading up to the signing of the Montreal Protocol, both in the expert and diplomatic arenas and as public diplomacy tools. We conclude by encouraging scholars to engage with new visual archives and to contribute to the development of the vibrant new field of research on visual diplomacy.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.017 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".