Protest in Style: Exploring Multimodal Concision in Rhetorical Artifacts
Bibliographic record
Abstract
Abstract This research explores two interconnected questions: (1) How do we approach stylistic features of multimodal rhetorical artifacts such as protest posters? (2) Do said artifacts designed for different purposes exhibit systematic stylistic differences? Drawing on Charles Sanders Peirce’s semiotic categorization, this study develops a framework for examining concision, one of the primary stylistic considerations for multimodal rhetorical artifacts such as protest posters. This paper illustrates the use of this framework by exploring the correlation between rhetorical purpose and concision in posters created and disseminated before and during the 2011–2012 Québécois student movement. This study fine-tunes our existing knowledge on multimodality with style sensitivity, and demonstrates how an economy-of-sign based semiotic approach could enrich the empirical examination of multimodal rhetorical artifacts by generating more controlled interpretations.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".