From Science to Governance: Understanding global warming controversies and politicization in nine dates
Bibliographic record
Abstract
The current global warming context is being experienced by world populations through the extreme whether events, sea level rise, loss of biodiversity, increase rise of temperature, reinsurgence of climate-related diseases and important slow and sudden-onset environmental catastrophes enhanced or accelerated by climate change among others.In such context, the global community, supported by evidenced science research are relentlessly calling for urgent climate actions to avoid reaching the point of non-return.Unfortunately, despite the fact that our planet continues to be under such threats of irreversible climate destruction, a fraction of scientists and political leaders motivated either by their nostalgic attachment to the carbondriven developmental era or pushed by the fossil fuel industry and its influential capacity on decision-making processes and decision-makers, continue to develop negationist theories, with the aim of creating skeptical mindsets and maintaining some doubts in public opinions as far as the very fact of global warming and the role of human activities in the occurrence of SCIREA Journal of Environment http://www.scirea.org/
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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 | 0.013 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.008 | 0.044 |
| Scholarly communication | 0.016 | 0.023 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".