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Record W2737626090 · doi:10.3390/su9081293

Climatic and Environmental Changes Affecting Communities in Atlantic Canada

2017· article· en· W2737626090 on OpenAlexafffundabout
Liette Vasseur, Mary J. Thornbush, Steve Plante

Bibliographic record

VenueSustainability · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsUniversité du Québec à RimouskiBrock University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCoastal floodFlooding (psychology)Storm surgeRelocationCoastal erosionGeographySustainabilityStormPopulationEnvironmental planningWork (physics)Climate changeGovernment (linguistics)Environmental resource managementTraining (meteorology)Environmental protectionFisheryEcologySea level riseEnvironmental scienceShore

Abstract

fetched live from OpenAlex

Small rural coastal communities located in Atlantic Canada are vulnerable to the effects of climate and environmental changes. Major storms have impounded the coastline, causing much physical damage and affecting the socioeconomics of these communities that are composed of an aging population. The current study relays findings based on interviews completed in 2011–2012, following the 2010 winter storms in Atlantic Canada. It portrays the physical and social–ecological impacts affecting 10 coastal communities located in the provinces of Québec, New Brunswick, and Prince Edward Island. Semi-structured interviews held in these provinces are the basis for the contributions of this research. The findings reveal physical changes related to coastal erosion from high-wave impacts and storm surge causing flooding of the coastal zone. Also considered are strategies preferred and actually implemented by residents, such as building of protection walls, although undesirable. Due to funding constraints, however, many of these large-scale flood protection projects are not possible without governmental support. Instead, it is suggested that development be controlled and some respondents in this study upheld that relocation be used to alleviate the situation. Finally, more work is required to improve emergency planning. Better concerted short- and long-term responses need to be coordinated by local authorities and higher up in the government in order to ensure the sustainability of these coastal 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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.281

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0120.002
Scholarly communication0.0020.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.056
GPT teacher head0.310
Teacher spread0.254 · 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 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

Citations22
Published2017
Admission routes3
Has abstractyes

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