Bibliographic record
Abstract
The Fifth Assessment Report by the Intergovernmental Panel on Climate Change (IPCC) was published in early 2014.In addition to expressing a "high confidence" in anthropogenic climate change, the report introduced a new emphasis on adapting to climate change.The Report's "Summary for Policymakers" declared, "Adaptation and mitigation are complementary strategies for reducing and managing the risks of climate change."Just a little later the report advises that, "Adaptation can reduce the risks of climate change impacts, but there are limits to its effectiveness…a longer-term perspective, in the context of sustainable development, increases the likelihood that more immediate adaptation actions will also enhance future options and preparedness." 1 In other words, adapting to the climate change that is underway is important, but to be effective, adaptation needs to take place in the context of sustainable development strategies.This highlights a recurring motif of the Fifth Assessment Report: adaptation now comes before mitigation.The IPCC still strongly recommends mitigating (i.e., reducing) global emission of greenhouse gases (GHGs).But there is also an urgent need to build what the Report, somewhat euphemistically, calls "adaptive capacity." 2 The overall message is clear: the effects of climate change are coming and we should try to keep them to a minimum, but people will be better able to cope with the effects if we begin to adapt to a warmer world right away.The next IPCC Assessment is not due until 2022.Four years is an eternity in climate change science and policy.To fill the gap, in 2018, the IPCC published a special report simply titled, Global Warming of 1.5°C.As the report's title suggests, the IPCC recommends that the global policy aim should be to limit climate change to 1.5°C above pre-industrial levels.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.036 | 0.005 |
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".