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Record W4221105090 · doi:10.21203/rs.3.rs-1348121/v1

Mapping the contours of an emerging phase out science

2022· preprint· en· W4221105090 on OpenAlexaff
Gregory Trencher, Adrian Rinscheid, Daniel Rosenbloom, Florentine Koppenborg, Nhi Truong, Pınar Temocin

Bibliographic record

VenueResearch Square · 2022
Typepreprint
Languageen
FieldEnvironmental Science
TopicHealth, Environment, Cognitive Aging
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComputer scienceData sciencePolitical scienceRegional scienceGeography

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.616
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.003
Scholarly communication0.0000.000
Open science0.0020.008
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0070.000

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.

Opus teacher head0.168
GPT teacher head0.467
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2022
Admission routes1
Has abstractyes

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