Bibliographic record
Abstract
The words “iconology” and “iconography” are often confused, and they have never been given definitions accepted by all iconographers and iconologists. Panofsky 1955 (cited under General Overviews) defines “iconography” as the study of subject matter in the visual arts and “iconology” as an attempt to analyze the significance of that subject matter within the culture that produced it. This definition was prescriptive rather than descriptive, and many art historians before Erwin Panofsky who would have called themselves “iconographers” were engaged in investigations that Panofsky would have termed “iconological.” Another source of semantic disagreement has arisen from the perceived overinterpretations of Panofsky and his school, which have led some art historians to reject the word “iconology.” It seems useful, nevertheless, to keep a distinction between iconography and iconology, since it draws attention to a fundamental distinction between the study of words and the study of images. While iconology corresponds to the historical criticism of texts in literary studies, iconography has no obvious counterpart outside histories of the visual. At the same time, in art historical practice iconography and iconology feed into each other, as the literature surveyed in this article shows.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.005 | 0.035 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".