Translating an Imagetext: Verbal and Visual Self-Representation in Brett Whiteley’s Interior, Lavender Bay (1976)
Bibliographic record
Abstract
This paper explores the relationship between the words and images in the drawing Interior, Lavender Bay by the Australian artist Brett Whiteley (1939-1992). This artwork combines the depiction of the artist’s home with a written element composed of the title, date, artist’s monogram, and a brief inscription. By examining Whiteley’s use of words and images in this drawing, the verbal/visual synergy that underpins his language is emphasized as a key aspect of his communicative appeal. The interpretive lens used in order to analyze Interior, Lavender Bay is interlingual translation. Translating Whiteley’s words from English into Italian allows not only to decipher the literal meaning and comprehend the symbolic function of his words, but also to highlight the relation between art and language. From this perspective, drawing on W. J. T. Mitchell’s Picture Theory (1994), the paper aims to discuss the functioning of images and the way in which interlingual translation might bring out latent connections in the source, opening a window on the interdisciplinary encounter between creative processes in the visual art and translation theory and practice.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.016 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".