MétaCan
Menu
Back to cohort
Record W4387129826 · doi:10.1080/00330124.2023.2250415

Public Perceptions of Resilience and Vulnerability Concepts for Adaptation

2023· article· en· W4387129826 on OpenAlex
Greg Oulahen, Christopher K. Randall, Calvin Nguyen, Carrie L. Mitchell

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueThe Professional Geographer · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsUniversity of WaterlooToronto Metropolitan University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsConceptualizationFraming (construction)Vulnerability (computing)SociologyGeographyResilience (materials science)Adaptation (eye)Political scienceSocial psychologyPsychologyComputer scienceComputer security

Abstract

fetched live from OpenAlex

Resilience is everywhere in plans, policy, and academic literature on risk reduction and adaptation, and a common refrain of elected officials and disaster victims alike. Geographers have contributed much to the critical understanding of the theoretical foundations and implications of this now ubiquitous concept, and have made some initial steps in studying how local practitioners and other experts interpret and apply resilience in risk reduction and adaptation measures. But there is limited empirical research, however, on what the people living in communities exposed to hazards think about resilience. This study aims to address this gap by conducting in-person, researcher-administered surveys (n = 400) with members of the public using coastal and lakefront environmental amenities in Vancouver and Toronto, Canada. Survey results include three main findings: (1) the majority of participants prefer the framing of “increasing resilience” over “reducing vulnerability”; (2) the conceptualization of resilience as creative transformation is greatly favored over conceptualizations of resilience as resistance or recovery; and (3) resilience is seen as uneven in both study cities. The study reveals insights that can help inform and align resilience theory and practice in cities.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.405
Threshold uncertainty score0.607

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 studies0.0010.001
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 head0.069
GPT teacher head0.384
Teacher spread0.315 · 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