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Record W2155081961 · doi:10.1017/s0032247412000320

When the river started underneath the land: social constructions of a ‘severe’ weather event in Pangnirtung, Nunavut, Canada

2012· article· en· W2155081961 on OpenAlexaffabout
Jennifer Spinney, Karen Pennesi

Bibliographic record

VenuePolar Record · 2012
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsWestern University
Fundersnot available
KeywordsVulnerability (computing)Social vulnerabilityFocus groupGeographyLocal governmentCoping (psychology)PerceptionGovernment (linguistics)Political scienceEnvironmental planningSociologySocial psychologyPsychologyPsychological resilienceComputer security

Abstract

fetched live from OpenAlex

ABSTRACT In June 2008, the community of Pangnirtung, Nunavut, Canada experienced a rainstorm that caused structural damage to the community's bridge and extensive permafrost erosion along the Duval River. The local government characterised the event as ‘severe’ and focused their attention on the bridge collapse, in contrast to the residents, who described this particular consequence as inconvenient at worst and at best, exciting. Instead residents expressed greater concern for the permafrost erosion and the uncertainty this posed for community well-being. This article follows an 11 week anthropological field trip to Pangnirtung in the summer of 2009 and is based on 31 semi-structured interviews, two focus group discussions, and participant observation. We explore how social processes influence subjective constructions of what constitutes ‘severe’ weather in the community, and attempt to explain how such constructions lead to differing perceptions of vulnerability to ‘severe’ weather events. Contributing factors including the normalisation of threat, local beliefs regarding change and uncertainty, as well as the communication of risk information are discussed along with the different coping strategies used by government and residents in managing their perceived levels of vulnerability. The research shows the importance of understanding the role social processes play in shaping local conceptions of ‘severe’ and perceptions of vulnerability to ‘severe’ weather events. This study enhances understandings of difference within populations and adds to the growing body of literature that demonstrates the need to incorporate locally relevant indices when conducting vulnerability assessment.

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 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 categoriesScience and technology studies, Insufficient 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 score0.303
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.032
GPT teacher head0.315
Teacher spread0.283 · 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 teacher head, not a consensus.

Study designObservational
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

Citations6
Published2012
Admission routes2
Has abstractyes

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