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Record W2891978349 · doi:10.2495/safe-v8-n4-493-504

Towards a conceptual framework for property level flood resilience

2018· article· en· W2891978349 on OpenAlex
Taiwo Adedeji, David Proverbs, Hong Xiao, Victor Oladokun

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Safety and Security Engineering · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicFlood Risk Assessment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsFlood mythResilience (materials science)Property (philosophy)Conceptual frameworkEnvironmental planningEnvironmental resource managementComputer scienceEnvironmental scienceSociologyGeographyEpistemologyMaterials scienceArchaeology

Abstract

fetched live from OpenAlex

Resilience is a multifaceted field of study that has been addressed by different disciplines and has been the subject of extensive research. Despite this vast body of research, there is no agreement on a single definition among researchers. Resilience in the context of flooding has become a major focus of flood risk management policy and reflected in current strategy to mitigate the effects of flooding. Furthermore, in recent times, increased attention has been given to property level resilience as part of an integrated approach to flood risk management. Despite this focus on resilience to flooding, there lacks a single definition and consequently, any effective means to quantify and measure resilience at the level of the individual property. This study aims to review and synthesize the concepts of resilience applied in different fields, in order to propose a resilience definition in the context of property level flood resilience. A framework for conceptualising flood resilience in residential property is developed which indicates the associated components and variables. The framework has the potential to be used by a range of key stakeholders in helping to understand current levels of property level resilience and in deciding what interventions might be best considered to improve resilience.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.809
Threshold uncertainty score0.234

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.015
GPT teacher head0.260
Teacher spread0.245 · 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