Mapping the contours of an emerging phase out science
Bibliographic record
Abstract
Abstract Phase-out has emerged as a policy approach to confront multiple sustainability crises. From ozone-depleting substances and hazardous chemicals to fossil fuels and transport technologies, phase-out experiences have been documented by diverse scientific communities. To consolidate this dispersed knowledge and inspire more systematic research, we map the evolution of scientific discussions about phase-out through a systematic literature review. Examining 870 papers published since 1970, we trace the evolving nature of phase-out strategies in terms of targets, geographic and industrial contexts, policy instruments and drivers. This provides a multi-faceted overview of an emerging and rapidly growing ‘phase-out science’ rooted across the full spectrum of scientific enquiry. Evolution of this science is marked by broadening engagement with a growing diversity of targets, contexts, and policies. Our analysis also shows how phase-out policies have recently gained momentum as a tool to tackle climate change, with a particular focus on fossil fuels and associated technologies.
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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 | 0.094 | 0.150 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.028 | 0.025 |
| Science and technology studies | 0.004 | 0.018 |
| Scholarly communication | 0.017 | 0.026 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".