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Record W4319342859 · doi:10.1371/journal.pclm.0000103

Understanding perceptions of climate vulnerability to inform more effective adaptation in coastal communities

2023· article· en· W4319342859 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

VenuePLOS Climate · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsNature Conservancy of CanadaUniversity of Victoria
FundersUniversity of Washington
KeywordsVulnerability (computing)Climate changeAdaptive capacityPerceptionEnvironmental resource managementSocial vulnerabilityVulnerability assessmentAdaptation (eye)GeographyEnvironmental planningPsychological resiliencePsychologyEcologySocial psychologyEnvironmental scienceComputer securityComputer science

Abstract

fetched live from OpenAlex

Coastal social-ecological systems are vulnerable to climate change with impacts distributed unequally amongst human communities. Vulnerability assessments, an increasingly popular methodology for understanding variability in vulnerability and its components, often fail to include or recognize the perceptions of individuals in the focal system. Perceptions of climate vulnerability are influenced by experiences, social networks, and cognitive biases, and often differ from vulnerability as measured by subject experts. Because perceptions influence human behavior, including if and how people take adaptive action, a failure to recognize perceptions can lead to ineffective adaptation plans and an incomplete understanding of system vulnerability. Here, as part of a novel, multi-method effort to evaluate vulnerability to climate change in the California Current social-ecological system, we survey fishers from Washington, Oregon, and California to understand their perceived vulnerability and investigate what factors drive variability in their views. We find that while there is a connection between some factors known to influence vulnerability of fishers, including vessel size and the diversity of fishing portfolios, the most significant predictor of higher perceived vulnerability was environmental worldview, specifically a belief that climate change is occurring. Motivation to adapt is also influenced by the sentiment that the impacts of climate change are more urgent and consequential than other problems; thus, we also evaluate how concern levels for environmental issues compare to other challenges that may affect fishing success and wellbeing. While just under half think that they will be personally harmed by climate change, generally the fishers were more concerned about issues like costs and regulations than they were about environmental impacts. This assessment of perceptions highlights the importance of communication and addressing cognitive barriers to adaptation in the effort to develop climate resilient fisheries and fishing communities in the United States.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.128
Threshold uncertainty score0.923

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.582
GPT teacher head0.461
Teacher spread0.120 · 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