'ut pictura poesis' and Aesthetic Kinship: A Case from Modern Arabic Prose
Bibliographic record
Abstract
This paper responds to the ancient question about the relationship - or lack of it – between history and art, avoiding the partiality of many single-talented disciples of these creative endeavors. This matter is examined in The Tattoo (Al-Washm, ´alwasm), a collection of prose narratives written by Hind Abu-Sha’ar, a Professor of history, a painter, a poet, and an established short story writer. It examines the effect that her versatile experience, as a historian and painter, has on her language, by tracing the historian-painter, not as character, but, rather, as the essential writer of her narratives. In particular, it investigates the interrelatedness of the scriptural, sculptural, visual, and historical in her stories where the painter and the historian cooperate in injecting their visions into the essence of the language textures of the narratives. Abu-Sha’ar’s versatile talent produces a distinctive utterance in which the advantages of painting and graphic art are employed to achieve a visual dimension in the lexicon as the scriptural becomes sculptural; and history is exploited to enrich the painted narratives with visions from the heritage of the past. Thus, rather than being a record of dead past times, history is turned into an ever-present live-picture by the language of painting, an achievement that uncovers a psychological vision of notions of memory and recall and, hence, of history.Keywords: ut pictura poesis; ekphrasis; Hind Abu-Sha'ar; artistic versatility; aesthetics
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.013 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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 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".