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Record W2021980312 · doi:10.1144/sp305.12

Hazard and vulnerability assessment and adaptive planning: mutual and multilateral community–researcher communication, Arctic Canada

2008· article· en· W2021980312 on OpenAlexaffabout
Norm Catto, Kathleen Parewick

Bibliographic record

VenueGeological Society London Special Publications · 2008
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsVulnerability (computing)HazardArcticEnvironmental resource managementVulnerability assessmentEnvironmental planningGeographyComputer scienceEnvironmental scienceComputer securityPsychologyEcologyBiologySocial psychology

Abstract

fetched live from OpenAlex

Abstract Communities in Arctic Canada are faced with natural geological and environmental hazards. Successful adaptation requires assessment of hazards from a physical science perspective, and appropriate communication with the communities. Transforming a hazard assessment exercise into an effective plan for adaptation requires an intimate cultural understanding. Hazard assessment involving substantial input from all research, administrative, socio-economic and cultural communities will lead to more appropriate and valuable analyses of risk, sensitivity and vulnerability. Residents and communities can contribute greatly to the identification and assessment of natural hazards. Community-driven communication is essential for meaningful risk analysis, adaptive planning and vulnerability assessment. Developing relationships with local media can be extremely beneficial. Using the practices of participatory community planning allows local environmental changes to be assessed and responded to by the people affected. Establishing effective working partnerships is essential for a true vulnerability assessment. The particularly sensitive nature of hazard assessments indicating increasing risk and vulnerability, and the continuing socio-economic changes in some communities, in the work described here, required consideration of the most appropriate methods of communication for each instance. The relationships that have emerged through the course of work in the communities have differed markedly from those originally envisioned, and also exhibit significant differences between communities.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.447

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0300.008
Scholarly communication0.0060.002
Open science0.0020.010
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.133
GPT teacher head0.403
Teacher spread0.270 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations7
Published2008
Admission routes2
Has abstractyes

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Same venueGeological Society London Special PublicationsSame topicIndigenous Studies and EcologyFrench-language works237,207