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Record W4225399211 · doi:10.1515/sem-2020-0113

The rhetorical dimension of images: identity building and management on social networks

2022· article· en· W4225399211 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSemiotica · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicSemiotics and Representation Studies
Canadian institutionsnot available
Fundersnot available
KeywordsRhetorical questionDimension (graph theory)Field (mathematics)Identity (music)SemioticsPersuasionSociologyPortraitEpistemologyAestheticsLinguisticsSocial psychologyPsychologyVisual artsArtPhilosophyMathematics

Abstract

fetched live from OpenAlex

Abstract This article proposes a semio-rhetorical epistemology for visual documents, one capable of accounting for both their internal configuration, which we shall call the compositional dimension, and their persuasive force within public space, or their rhetorical dimension. The field of reference will be that of identity-related images on social networks, because compared to other kinds of images, such as artistic or professional ones, they adopt new compositional solutions and new dynamics of circulation. To test this theoretical framework, we will conduct an analysis which has never been carried out in semiotics and which, as far as we know, remains very rare even in the overall field of visual studies, that is, the analysis of the profile of an Instagram influencer’s visual production, that of Canadian artist Rupi Kaur. Taking into account the flow of images shared over time, we will focus primarily on the compositional dimension that articulates the specificity of the language of images. The most appropriate model for investigating social network photos seems to be that of the portrait, thanks to which we will identify a first series of regularities and deviations. Secondly, we will turn towards the rhetorical dimension – the persuasive strategies found within, through, and towards images – focusing on the analysis of a single photo: on the one hand, it is a shot which presents greater compositional richness than others; on the other hand, it has greatly impacted the notoriety of the influencer, due to the censorship incurred on Instagram, its abundant coverage by traditional media, and the heated debate it triggered on social media. We will thus propose a reinterpretation of Paul Ricœur’s theory of identity in order to balance the rhetorical and the compositional dimensions through a unitary theoretical hypothesis. Visual identity on social networks is always the result of a negotiation between two opposite tendencies: on the one hand, the experiential pressure expressed through images related to the body and everyday practices; on the other, the algorithmic pressure due to the delegation of the management of identity to software. The case of Rupi Kaur is a rare example of a critical mediation between these two pressures and helps us build a methodology for the examination of images belonging to other social domains.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.917
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.046
GPT teacher head0.300
Teacher spread0.255 · 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