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Record W4320486848 · doi:10.1016/j.crm.2023.100487

Risk from responses to a changing climate

2023· article· en· W4320486848 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueClimate Risk Management · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Geoengineering
Canadian institutionsnot available
FundersForeign, Commonwealth and Development OfficeAfrican Academy of SciencesRoyal SocietyInternational Development Research CentreNational Socio-Environmental Synthesis Center
KeywordsMaladaptationClimate changeVulnerability (computing)HazardEnvironmental resource managementRisk analysis (engineering)Environmental planningEnvironmental scienceBusinessComputer scienceEcologyPsychologyComputer security

Abstract

fetched live from OpenAlex

Effectively responding to intensifying climate change hazards requires identifying risks arising from each response, as well as risks arising from the dynamic interactions between responses. Using examples of managed retreat and solar geoengineering, we illustrate the importance of understanding response as a determinant of climate change risk. We highlight a continuum of severity of response risks, both at the site of deployment and across temporally and geographically distant contexts. While responses might moderate a specific hazard, due to the complexity of climate change risk they may be ineffective at reducing net climate-related risk for any given actor or system. We also show how some responses to climate change affect vulnerability, exposure, and other responses to climate change independent of the targeted hazard and can lead to maladaptation. We conclude by emphasizing the importance of integrating climate change responses together with other determinants of risk to better inform climate risk management and guide research on the feasibility of individual response options.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.175
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.023

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 head0.016
GPT teacher head0.246
Teacher spread0.230 · 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