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Record W3166416883 · doi:10.1017/s0008423921000305

Au cœur de la tempête : L'opinion publique électorale et la crise des réfugiés

2021· article· fr· W3166416883 on OpenAlexaffabout
David Dumouchel

Bibliographic record

VenueCanadian Journal of Political Science · 2021
Typearticle
Languagefr
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Résumé La littérature sur les tempêtes médiatiques n'a jamais évalué leurs effets sur l'opinion publique de manière systématique. Cet article vise à combler ce vide en mobilisant des données de sondage pour évaluer l’évolution de l'opinion publique en regard de la crise des réfugiés, une tempête médiatique survenue durant la campagne fédérale canadienne de 2015. Les résultats montrent que la période de tempête médiatique a influencé les attitudes citoyennes à l’égard de certains cadres liés à la question et que l'effet a persisté jusqu’à la fin de la campagne. Ils révèlent par ailleurs que certaines opinions politiques en viennent à constituer des éléments déterminants de l'intention de vote et du choix de vote final. Ces éléments de preuve montrent que les citoyens sont réceptifs aux tempêtes médiatiques et constituent un exemple concret de la manière dont la logique de marché médiatique devient parfois prépondérante dans les rapports de force qui caractérisent la sphère publique.

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)0.006
metaresearch head score (Gemma)0.036
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 score0.041
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.036
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.003
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0150.001

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 head0.025
GPT teacher head0.358
Teacher spread0.333 · 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

Citations1
Published2021
Admission routes2
Has abstractyes

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Same venueCanadian Journal of Political ScienceSame topicDisaster Management and ResilienceFrench-language works237,207