Mitigation strategies to enhance the ambition of the nationally determined contributions : an analysis of 4 European countries with the decarbonization wedges methodology
Bibliographic record
Abstract

 Greater efforts are needed to bridge the emission gap between Nationally Determined Contributions and the objective to limit climate change below 2°C. This paper focuses on four European-Union countries: Germany, France, Poland and UK that represent on aggregate 55% of current EU emissions. It analyses national mitigation strategies produced by national research teams in the framework of the COP21_RIPPLES project and compatible with a long-term objective leading to a well below 2°C target either as part of an ambition in 2030 limited to that of the NDCs, or as part of more ambitious early action. We use the decarbonization wedges methodology, an advanced index decomposition analysis methodology for quantifying the contribution of different mitigation strategies. This makes it possible to assess the priorities for action to strengthen the NDCs. The article also highlights the impact sectoral growth dynamics have on the emission trajectories and the resulting necessary mitigation efforts.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".