Bibliographic record
Abstract
One very simple truth about Global Warming is this, that it will spare nobody, however rich, mighty and powerful we think we are. … Mr Tony Blair, the Prime Minister of the UK once said that without proper action now, the average global temperatures would rise by 2 degrees Celsius. Scientists estimate that the subsequent rise in the sea level would be enough to swamp a large proportion of Bangladesh in 30/40 years time. It would be a serious catastrophe for my country and for the whole region if much of the land in Bangladesh disappears under the sea. I become frightened to think that my grandchildren (when I touch them) will have no place to live on this planet earth. I really want to be sure that my grandchildren, and their children after them, will be able to enjoy the beauty of my country that I have enjoyed, and be able to have enough land to live, and enough land for food. Michael S. Baroi, Anglican Bishop of Bangladesh Introduction For some observers, climate change is the single most important public policy challenge of our time. But describing the ‘problem’ is not actually an easy matter. It is dizzying in its complexity, daunting in its implications, and multifaceted in a way that eludes easy categorization. Beginning with the environmental dimension, global warming is a problem of unprecedented scale. It is planetary in scope and inter-generational in its implications. Even more importantly, because climate change implicates virtually all production and consumption processes, addressing it is about nothing less than changing the way we do everything that we do, everywhere in the world. Climate change, then, is also a classic collective action problem. It can only be solved if all states, or at least the major greenhouse gas emitters, cooperate. These difficulties are compounded by the fact that far-reaching decisions must be made under conditions of scientific uncertainty. While both the phenomenon of human-induced climate change and its dangerous potential are now beyond doubt, that was not always the case. On other issues, such as the speed and severity of climatic change, some debate continues. Not surprisingly, therefore, global warming is also an intractable political problem. How does one get states and political leaders to prioritize the issue, nationally and internationally?
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.146 | 0.060 |
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".