Icons and metaphors in visual communication: The relevance of Peirce’s theory of iconicity for the analysis of visual communication
Why this work is in the frame
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Bibliographic record
Abstract
In this paper we adopt Charles Sanders Peirce’s concept of iconicity to analyse pictural communication. While visual semiotics has a well-developed structural school, the concepts of visual semiotics stemming from Peirce’s pragmatic sign theory are often overlooked. The specific purpose of this study is to explore the semiotics of visual signs, exemplified by two prominent pictures of former US President Donald Trump. We argue that Peirce’s semiotic framework for iconicity in visual signs (the image, the diagram, and the metaphor) offers a useful framework for discussing how the meaning of visual signs is motivated. On this basis, we propose that Peirce’s concept of hypoicons provides us with a richer understanding of how visual signs acquire meaning and how their interpretation varies across cultural habits, and collateral experience.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it