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Record W3157816164 · doi:10.47389/36.2.19

Understanding and improving community flood preparedness and response: a research framework

2021· article· en· W3157816164 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

VenueAustralian Journal of Emergency Management · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicFlood Risk Assessment and Management
Canadian institutionsSydney Steel (Canada)
Fundersnot available
KeywordsPreparednessProject commissioningFlood mythEmergency managementEnvironmental planningPublishingEnvironmental resource managementPsychological interventionPolitical scienceGeographyEnvironmental sciencePsychology

Abstract

fetched live from OpenAlex

Many social research projects identify issues with community disaster preparedness and response but struggle to attribute these issues to underlying causes and recommend possible ways to address them. A research framework that considers the underlying causes of preparedness and response and possible interventions was developed for the Wimmera region of Victoria, Australia. The research framework was developed in conjunction with the Wimmera Catchment Management Authority and tested in a social research project across 6 communities in the Wimmera region. This paper provides an outline and rationale for the components of the research framework. It also summarises the regional flood insight afforded by the research framework. The research framework, albeit with some limitations, has universal appeal not only in the examination of community flood preparedness and response, but also for other hazards and other parts of the disaster management cycle.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.298
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.247
GPT teacher head0.394
Teacher spread0.147 · 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