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Record W4417045756 · doi:10.7202/1122027ar

Local Knowledge in Resilience and Adaptation to Snowstorm Hazards in Two North Atlantic Islands: Newfoundland and Iceland

2023· article· en· W4417045756 on OpenAlexaffvenueabout
Michelle Valliant

Bibliographic record

VenueNewfoundland and Labrador Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsAdaptation (eye)Psychological resilienceHazardCommunity resilienceResilience (materials science)Traditional knowledgeStormClimate change

Abstract

fetched live from OpenAlex

Drawing on first person observations, this paper explores how severe winter storms impacted the two rural island communities of Newfoundland and Iceland in January of 2020. The authors, as researchers and local community members, examine vulnerability, resilience, and adaptation as processes of community transformation in response to large-scale environmental hazards. Highlighting the significance of local knowledge and place-based worldviews, we argue that community-driven interactions are more effective than top-down approaches for hazard reduction and climate change adaptation. Our observations aim to offer broader insights for regions with similar socio-cultural and environmental contexts, underscoring how localized perspectives can foster positive transformation and strengthen adaptive capacity.

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.

How this classification was reachedexpand

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.885
Threshold uncertainty score0.980

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 studies0.0000.001
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 head0.031
GPT teacher head0.335
Teacher spread0.303 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes3
Has abstractyes

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