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Record W4312059529 · doi:10.1016/j.crm.2022.100471

Climate-driven risks to peace over the 21st century

2022· article· en· W4312059529 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueClimate Risk Management · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicTransboundary Water Resource Management
Canadian institutionsCarleton University
FundersHORIZON EUROPE European Research CouncilEuropean Research CouncilEuropean Commission
KeywordsClimate changeAdaptation (eye)Scale (ratio)Global warmingEnvironmental resource managementEnvironmental ethicsPolitical scienceEnvironmental planningEnvironmental sciencePsychologyGeographyEcology

Abstract

fetched live from OpenAlex

Anthropogenic climate change is commonly characterized as a threat to human security. However, the extent to which and under what conditions climate impacts and responses may produce severe risks to peace have seen less systematically assessment to date. This essay provides a conceptual discussion of what risks to peace entail and how such risks might be considered severe, acknowledging that perceptions, values, and social scale must be grappled with in the identification of severity. Informed by available empirical research, the essay then explores the conditions under which climate-related risks could become severe during this century. Three illustrative scenarios based on different assumptions about climate-driven risks and risks related to social responses to climate change serve to illustrate how alternative warming and adaptation trajectories will have distinct implications for the prospect of future peace. The essay ends by reflecting on some implications for future research needs.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.843
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0050.000
Scholarly communication0.0000.000
Open science0.0020.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.023
GPT teacher head0.297
Teacher spread0.273 · 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