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Record W30243353 · doi:10.1016/j.cgh.2018.05.017

Celebrity and credibility in environmental communication

2011· article· en· W30243353 on OpenAlexaboutno aff
Valérie Brière

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicRhetoric and Communication Studies
Canadian institutionsnot available
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institutes of Health
KeywordsCredibilityPersuasionRhetoricEthosRhetorical questionGovernment (linguistics)PopulationPower (physics)Political scienceSource credibilityPublic relationsSociologyLawPsychologyArtSocial psychology

Abstract

fetched live from OpenAlex

In summer 2010 Quebec’s government undertook the exploration phase of shale gas exploitation in the St-Lawrence valley, leading to a wave of protests coming from the non-consenting and ill-informed population. Thus, this paper presents a rhetorical analysis of a video produced by famous Quebec artists advocating for a moratorium regarding shale gas exploitation in Quebec. It aims to understand the influence of source credibility on the video’s reception as well as the power of ethos in the persuasion process that led to the signature of an online petition in favour of the shale gas project’s suspension. Therefore, with the help of rhetoric, attitude change and source credibility theories, this analysis focuses on the source, the message and its style, the audience and the delivery to identify the means of persuasion of this video. The result of this research indicates that the video director has indeed succeeded in building a strong case and managing the source credibility to its advantage through the art of rhetoric.

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)0.009
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.021
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.033
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.002
Science and technology studies0.0080.013
Scholarly communication0.0100.006
Open science0.0010.004
Research integrity0.0030.003
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 head0.094
GPT teacher head0.213
Teacher spread0.119 · 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 designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2011
Admission routes1
Has abstractyes

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