Global Warming and Climate Change: What Australia knew and buried...then framed a new reality for the public
Bibliographic record
Abstract
After many years spent as a journalist, editor and documentary film maker covering environmental and rural issues, I landed for an exciting spell of longform research at the Australian National Centre for the Public Awareness of Science.My mission became to explore a hitherto unasked question that required ranging widely across science and the humanities: how could we, as a society, have buried what we once knew about the risk to everyone of global warming and climate change?This investigation was granted the necessary time through support from The Australian National University and the Commonwealth.I am indebted to the journalists, scientists, policy-makers and researchers who put on the documentary record the outline of Australia's response to global warming and climate change since the 1980s.I am similarly indebted to those, particularly from the United States, who documented a parallel arc of public knowledge and official response over the past 25-30 years.The story that unfolded found strong echos in other countries with similar economics and politics.You will find many names with attribution in the pages of this book.Their contributions to the national and international conversation are significant.Far from 'yesterday's news', they bore witness to today's history and how we communicated it along the way.Public documents were the bedrock of this investigation and I am indebted also to the late Deni Greene and to the ACT Environment Centre for their super document collections showing Australia's early response to climate change knowledge.Thanks also to those who kindly granted interviews that expanded the documentary record.Finally, but not least, I thank my family, friends and professional colleagues who gave generously of their time, talent, ideas and encouragement to get this story told.
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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 | 0.002 | 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".