Global Warming and Climate Change: What Australia knew and buried...then framed a new reality for the public
Bibliographic record
Abstract
1988: coming to grips with a terrifying global experiment \nThe Toronto conference statement made it clear that climate change would affect everyone. It called greenhouse gas atmospheric pollution an ‘uncontrolled, globally pervasive experiment whose ultimate consequences could be second only to nuclear war’. World governments were urged to swiftly develop emission reduction targets (The changing atmosphere: implications for global security, 1988).\nRelevant to both Australian and overseas audiences, here is the untold story of how Australia buried its knowledge on climate change science and response options during the 1990s — going from clarity to confusion and doubt after arguably leading the world in citizen understanding and a political will to act in the late 1980s. ‘What happened and why’ is a fascinating exploration drawing on the public record of how a society revised its good understanding on a critical issue affecting every citizen. It happened through political and media communication, regardless of international scientific assessments that have remained consistent in ascribing causes and risks since 1990. How could this happen? The author examines the major influences, with lessons for the present, on how the story was reframed. Key have been values and beliefs, including economic beliefs, that trumped the science, the ability of changing political leaders and the mass media to set the story for the public, as well as the role of scientists’ own communication over time and the use and misuse of uncertainty.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.016 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".