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Record W3027674571 · doi:10.1016/j.oneear.2020.04.011

Conceptualizing Climate Vulnerability in Complex Adaptive Systems

2020· article· en· W3027674571 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueOne Earth · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicClimate change impacts on agriculture
Canadian institutionsUniversity of Northern British Columbia
FundersEconomic and Social Research CouncilCrown-Indigenous Relations and Northern Affairs CanadaUK Research and Innovation
KeywordsVulnerability (computing)Climate changeClimate systemVulnerability assessmentEnvironmental resource managementAdaptive capacityEnvironmental planningComputer scienceGeographyEnvironmental sciencePsychologyComputer securityGeologyOceanographySocial psychologyPsychological resilience

Abstract

fetched live from OpenAlex

This Perspective develops a novel approach for assessing the vulnerability of complex adaptive systems to climate change. Our characterization focuses on the dynamic nature of vulnerability and its role in developing differential risk across multi-dimensional systems, communities, or societies. We expand on past conceptualizations that have examined vulnerability as processual rather than a static or binary state and note the necessary role of complexity and complex adaptive systems theory as a basis for effective vulnerability assessment. In illustrating our approach, we demonstrate the importance of factors such as modulation (connectedness), feedback mechanisms, redundancy, and the susceptibility of individual components within a system to change. Understanding the complexity of potentially vulnerable systems in this manner can help unravel the causes of vulnerability, facilitate the identification and characterization of potential adaptive deficits within specific dimensions of complex adaptive systems, and direct opportunities for adaptation.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.923
Threshold uncertainty score0.882

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.197
GPT teacher head0.270
Teacher spread0.072 · 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