Essential outcomes for COP26
Bibliographic record
Abstract
The UK Government is hosting COP26 in Glasgow between 31st October and 12th November 2021. It plans to make progress in four key areas which summarize as ‘coal, cars, cash and trees’ (Carbon Brief, 2021). The first two of these aims—to get agreement for the rapid phase out of coal, the most polluting of fossil fuels, and to ensure a rapid transition away for cars fuelled by fossil fuels—are very important, but are not directly related to the remit of Global Change Biology. The latter two aims—ensuring that the financial support of $100 billion per year promised in 2010 by wealthy countries to developing countries finally gets delivered and ensuring that climate solutions adopted also co-deliver to nature—are squarely within the remit of Global Change Biology. With respect to the ‘cash’ aim, this flow of finance is essential to allow poorer countries to adapt to, and to mitigate, climate change. We know that a vast proportion of the potential for natural climate solutions is located in the developing world (Griscom et al., 2020), so if we are to realize that global potential, developing countries must have the financial backing to ensure that this happens in an equitable and just way. Not all of this cash will be used for nature-based solutions, of course, but a proportion of it will be, and nature-based solutions would almost certainly not happen at the scale and speed required to help us meet net zero greenhouse gas emissions targets without this cash. With respect to the ‘trees’ aim, the first thing to note is that nature-based solutions are about so much more than just planting trees (Seddon et al., 2021)! ‘Trees’ is just shorthand for nature-based solutions, but the broad variety of nature-based solutions available, beyond just tree planting, must be encouraged at COP26. The recent joint workshop report by IPBES and IPCC (Pörtner et al., 2021) demonstrated that we cannot successfully resolve either of the existential threats of climate change or biodiversity loss unless we tackle them both together. Mainstreaming nature into our thinking on climate action is essential, so encouraging all countries to include nature-based solutions in their nationally determined contributions to meet the goal of the Paris Agreement will be the first step in formalizing these considerations. COP26 provides the promise of progress for climate change and nature, and for kickstarting the urgently required transition from pledges to real-world action. Time is running out—so we watch with interest to see whether this promise can be converted into concrete action. The authors declare no conflict of interest. Data sharing not applicable—no new data generated, or the article describes entirely theoretical research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".