Paintings as “Visual Poetry”: Diagrammatic Iconicity in the Art of Juan Miró
Bibliographic record
Abstract
Conceptual Metaphor Theory (Lakoff and Johnson, 1980) and work on multimodal metaphors (Forceville, 2006) has opened up a new approach to the study of language and other modalities. However, relatively few cognitive linguistic investigations of visual art have been performed. We analyzed paintings done by Spanish Surrealist Juan Miró (1893-1983), focusing on diagrammatic iconicity, i.e. how his pictorial elements are arranged structurally in ways that correspond to their meaning. In particular, we examined the artist’s paintings between 1940 and 1970, based on the model advanced by Hiraga (2005). Our results show that iconic mappings like SIMILARITY IN MEANING IS SIMILARITY IN FORM, MORE CONTENT IS MORE FORM, and SEMANTIC RELEVANCE IS CLOSENESS, function as cognitive principles prevalent in these paintings. The current study therefore supports the proposal that diagrammatic iconicity operates across different semiotic systems, and at the same time contributes to the description and explanation of artistic practices involving language and painting.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".