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Record W2291508847 · doi:10.5539/ijel.v6n1p100

Appeals to Ethos and Pathos in Post-Crisis Communication: A Case Study of Press Conferences Handling Tianjin Blasts

2016· article· en· W2291508847 on OpenAlexvenueno aff
Xueyu Wang

Bibliographic record

VenueInternational Journal of English Linguistics · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Relations and Crisis Communication
Canadian institutionsnot available
Fundersnot available
KeywordsPathosEthosRhetorical questionContext (archaeology)CredibilityRhetoricLogos Bible SoftwarePersuasionRhetorical deviceSociologyPolitical scienceSocial psychologyMedia studiesPsychologyLawLinguisticsHistoryPhilosophyTheology

Abstract

fetched live from OpenAlex

<p>This study focuses on the rhetorical appeals in post-crisis communication, and analyzes the influence of dynamically changing context on the speakers’ choice of rhetorical means. Aristotle’s three important rhetorical appeals-ethos, pathos and logos are investigated in the transcript of 14 press conferences handling Tianjin blasts. The changes in speakers’ rhetorical appeals are explored in relation to the changing context in the evolving crisis. In post-crisis press conferences, the speakers most frequently used appeals to ethos and pathos to persuade. Specifically, when appealing to ethos, the speakers usually manipulated discursive resources to construct their credibility, expertise, and similarity with the audience; when appealing to pathos, such emotions of the public as the feelings of depression, need for appreciation, and expectation for a thorough investigation of the blasts were addressed. In addition, as the crisis unfolded, the context for communication was dynamically changing. There was a tendency for speakers to adapt their rhetorical appeals to the dynamically changing context.</p>

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)0.002
metaresearch head score (Gemma)0.039
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.220
Threshold uncertainty score0.969

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.039
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.039
GPT teacher head0.368
Teacher spread0.329 · 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 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

Citations3
Published2016
Admission routes1
Has abstractyes

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