Assessing Science-Based Decision-Making in US Climate Change Lawsuits

John M. Doherty et al.

Journal of Environmental Law2025https://doi.org/10.1093/jel/eqaf002article
ABDC B
Weight
0.50

Abstract

Judges in US state courts are increasingly presiding over lawsuits that involve disputes related to climate change. This gives the courts an important role in helping shape climate governance. However, the extent to which judges choose to engage with relevant scientific information when deciding climate cases is unclear. To understand how science informs judicial decision-making, we analyse the language of court documents from 68 climate cases across seven politically distinct US states. We conclude with three major takeaways. First, we find that high levels of engagement with science tend to correlate to what we call ‘positive’ climate outcomes, that is; outcomes that favour an analysis or reduction of greenhouse gas emissions. Second, we report that technical content introduced by legal parties and scientific resources published by state agencies are frequently cited sources of science. Third, we find that claims regarding environmental rights and involving adaptation and mitigation disputes gave rise to the highest levels of judicial engagement with climate science. Ultimately, these findings highlight the key role that science plays in informing judicial decision-making, despite considerable political and policy diversity among the investigated states.

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https://doi.org/https://doi.org/10.1093/jel/eqaf002

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@article{john2025,
  title        = {{Assessing Science-Based Decision-Making in US Climate Change Lawsuits}},
  author       = {John M. Doherty et al.},
  journal      = {Journal of Environmental Law},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1093/jel/eqaf002},
}

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Assessing Science-Based Decision-Making in US Climate Change Lawsuits

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.