Virtual Topography: Poets, Painters, Publishers and the Reproduction of the Landscape in the Early Nineteenth Century
Bibliographic record
Abstract
In this article I develop the work of a number of critics—Gillen Darcy Wood, Sophie Thomas, Peter Simonsen, Julia S. Carlson—who have recently begun to revise our understanding of the relationship of literary Romanticism, and in particular that of Wordsworth and Southey, to visual culture. I show first that new means of mechanical reproduction—the woodcut, the aquatint—combined with technological changes in book production, stimulated a new print genre known asViews—an ancestor of the coffee-table book and often a spin-off wherein the public could see engravings of the scenes their favourite landscape poets described. Pictures sold poets, and, for the first time in history, popular writers were marketed to a mass readership able—and avid—to buy images as well as words. Wordsworth and Southey were not popular writers and were not at first marketed as illustrated poets. And they at first disapproved of the visual turn of their culture. This disapproval, I show, was never consistent or total and in fact they strove to take advantage of the vogue for the visual, collaborating with artists to publish volumes ofViewsin which their writing was combined with engravings of landscape. And these collaborations, I argue, were greatly influential upon them, causing them to alter the form and style of their writing as well as the publication formats in which it appeared. Wordsworth and Southey, in their late work, became writers of a moralised picturesque—of words that deferred to pictured views and tourist sights—and that sought to derive truths about human nature, life and society from them. Departing from their earlier suspicion of the visual, and ofViews, they became practitioners, in conjunction with artists, of a virtual topography. Their continued marketing, in the 21stcentury, as part of the visual packaging of the Lake District in picture-book, DVD, and website is therefore not as contrary to what they stood for as it first might seem, shallow though it often is.
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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 | 0.002 |
| Science and technology studies | 0.005 | 0.017 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".