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Record W2106277313 · doi:10.1111/cag.12141

Analyse des perceptions de l'exposition au changement climatique de deux localités canadiennes

2015· article· fr· W2106277313 on OpenAlexaffvenueabout
Jonathan Leblanc Tanguay, André Viau

Bibliographic record

VenueCanadian Geographies / Géographies canadiennes · 2015
Typearticle
Languagefr
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPolitical scienceHumanitiesGeographyForestryPhilosophy

Abstract

fetched live from OpenAlex

Le Groupe Intergouvernemental d'experts sur l'Évolution du Climat prévoit que le changement climatique se manifestera par une augmentation de la température moyenne mondiale de 2 °C au courant du 21esiècle. Une conséquence du réchauffement prévoit un accroissement dans l'intensité et la fréquence des extrêmes météorologiques dans la région sud‐ouest du Québec, au Canada. Une évaluation des vulnérabilités aux changements climatiques de Mont‐Laurier et de Ferme‐Neuve a été entreprise à l'été 2011. Un total de 25 entrevues et un groupe de discussion ont été conduits auprès des deux populations, ce qui a permis de mettre en relation les expériences et les connaissances locales avec les projections climatiques et socio‐économiques. L'étude souligne l'importance de la diversification des activités économiques et de la population dans la relation entre le climat et le milieu local. Une composition démographique et une économie non diversifiées exposent les deux municipalités aux aléas du climat. Un changement dans la dynamique entre le contexte socio‐économique et biophysique tend à exposer davantage Ferme‐Neuve aux impacts potentiels du changement climatique. Cependant, une étude plus approfondie de la capacité d'adaptation doit être conduite auprès des deux communautés afin d'évaluer leurs vulnérabilités respectives

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)0.002
metaresearch head score (Gemma)0.004
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 score0.615
Threshold uncertainty score0.765

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.143
GPT teacher head0.335
Teacher spread0.192 · 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

Citations1
Published2015
Admission routes3
Has abstractyes

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