Classifying global catastrophic risks
Open accessAbstract
We present a novel classification framework for severe global catastrophic risk scenarios. Extending beyond existing work that identifies individual risk scenarios, we propose analysing global catastrophic risks along three dimensions: the critical systems affected, global spread mechanisms, and prevention and mitigation failures. The classification highlights areas of convergence between risk scenarios, which supports prioritisation of particular research and of policy interventions. It also points to potential knowledge gaps regarding catastrophic risks, and provides an interdisciplinary structure for mapping and tracking the multitude of factors that could contribute to global catastrophic risks.
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A risk is composed of hazards, vulnerabilities, and exposure, not just individual threats.
“Second, a risk is composed of hazards, vulnerabilities, and exposure, not just individual threats (IPCC, 2012; Avin et al., 2018; Currie and Ó hÉigeartaigh, 2018; Liu et al., 2018).”
From A Fate Worse Than Warming? Stratospheric Aerosol Injection and Global Catastrophic Risk (2021) · cites this paper as Avin et al., 2018
The Abstract says the framework goes beyond individual risk scenarios, supporting the claim that risk is not just a matter of individual threats. But it names critical systems affected, global spread mechanisms, and prevention and mitigation failures as its three dimensions—not hazards, vulnerabilities, and exposure. (LLM, conf=0.86)
Experimental — accuracy not yet measuredAlternative frameworks for classifying global catastrophic risks have yet to be widely adopted.
“While there have been some alternative frameworks for classifying GCRs (Avin et al., 2018; Liu et al., 2018; Baum and Barrett, 2019), these have yet to be widely adopted.”
From A Fate Worse Than Warming? Stratospheric Aerosol Injection and Global Catastrophic Risk (2021) · cites this paper as Avin et al., 2018
The Abstract identifies this paper as proposing a framework for classifying global catastrophic risks, supporting its citation as an example of an alternative framework. Neither the Abstract nor §6, “Where to next?”, assesses whether such frameworks have been widely adopted; §6 discusses hoped-for future uses instead. The adoption claim is therefore not supported by this source. (LLM, conf=0.84)
Experimental — accuracy not yet measured
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Comparison between TED Talks and scientific articles: global catastrophe risks
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Fisher, L., & Sandberg, A. (2022) · Journal and proceedings of the Royal Society of New South Wales · doi:10.5962/p.389580
Beard, S., Rowe, T., & Fox, J. (2024) · Open Book Publishers · doi:10.11647/obp.0360.06
- Authors
- Avin, S., Wintle, B. C., Weitzdörfer, J., Ó hÉigeartaigh, S. S., Sutherland, W. J., & Rees, M. J.
- Affiliations
- University of Cambridge (GB)
- Corresponding author
- Avin, Shahar
- Venue
- Futures
- Publisher
- Elsevier BV
- Published
- 2018-09
- Volume
- 102
- Pages
- 20-26
- ISSN
- 0016-3287 (ISSN-L)
- OpenAlex
- W2789287982
- Cited by
- 116
- References
- 16
- Citations by year
- 2026: 6 · 2025: 16 · 2024: 18 · 2023: 21 · 2022: 18 · 2021: 13 · 2020: 12 · 2019: 7 · 2018: 5
- FWCI
- 21.05
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Futures (publishedVersion, cc-by)
- Apollo (University of Cambridge) (submittedVersion, cc-by)
- Apollo (cc-by)
- Funders
- Arcadia Fund
- Templeton World Charity Foundation
- Topics
- Social Sciences › Sociology and Political Science › Risk Perception and Management
- Social Sciences › Sociology and Political Science › Disaster Management and Resilience
- Social Sciences › Political Science and International Relations › Nuclear Issues and Defense
- Keywords
- global catastrophic risk, risk classification, critical systems, risk prioritization, policy interventions, knowledge gaps
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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