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Record W2506319713 · doi:10.5539/ijel.v6n4p30

A Multimodal Discourse Analysis of Air France’s Print Advertisement

2016· article· en· W2506319713 on OpenAlexvenueno aff
Chunyu Hu, Mengxi Luo

Bibliographic record

VenueInternational Journal of English Linguistics · 2016
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsnot available
FundersCivil Aviation Administration of ChinaMinistry of Education of the People's Republic of China
KeywordsAdvertisingProsperityPopularityPromotion (chess)BusinessCompetition (biology)Atmosphere (unit)EntertainmentMarketingAdvertising campaignBrand imageQuality (philosophy)Political scienceGeographyLaw

Abstract

fetched live from OpenAlex

<p>The past decade has witnessed the rising popularity of the airline industry, along with prosperity and ever increasing competition. It has become important for airline companies to outshine their rivals for a favorable market share. As a major means of promotion, advertising campaign is of crucial importance in building the corporate image and exerting brand influence. This study conducts a multimodal discourse analysis on the advertising campaign launched by Air France in 2014, and hope to be of interest to researchers, producers of advertising metaphors, as well as consumers in general. The results indicate that the highlighted visual and textual components are arranged as such to form a sense of superiority and great comfort that is perceivable to the viewers. Through the construction of an elegant, glamorous and superior atmosphere, it is palpable that Air France tends to broadcast their brand toward viewers who pay attention to quality of and enjoyment in life, and welcome prosperous cultural peculiarities.</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)0.000
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.330
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.012
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.323
Teacher spread0.311 · 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 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

Citations5
Published2016
Admission routes1
Has abstractyes

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Same venueInternational Journal of English LinguisticsSame topicLanguage, Metaphor, and CognitionFrench-language works237,207