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Record W3196656351 · doi:10.1111/1745-5871.12503

Crisis management: Regional approaches to geopolitical crises and natural hazards

2021· article· en· W3196656351 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

VenueGeographical Research · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsBrock University
FundersAustralian Research CouncilUniversity of the Sunshine Coast
KeywordsGeopoliticsCrisis managementCorporate governanceNatural hazardPoliticsPolitical scienceNatural (archaeology)Regional scienceNatural disasterGeographyEnvironmental resource managementEconomicsManagement

Abstract

fetched live from OpenAlex

Abstract Crisis management planning and response can be improved by regional governments and organisations learning from one another. Specifically, comparative learning may be a benefit when groups understand the perceived effectiveness of various regional approaches when responding to different types of hazards. This article presents findings from a comparative case study analysis of regional governance perspectives of crisis management for geopolitical events and natural hazards in the Sunshine Coast, Australia, and Gotland, Sweden. Data were collected and analysed using document analyses and semi‐structured interviews with regional practitioners. It was found that regional crisis management is increasingly influenced by global processes that are affecting the scales and characteristics of crises. As a result, prospective regional governance must evolve to include more international perspectives in crisis management and account for activities and processes that take place beyond arbitrary political boundaries.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.797
Threshold uncertainty score0.735

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.218
GPT teacher head0.408
Teacher spread0.191 · 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