Nationalism and Pre-Raphaelite Art
Bibliographic record
Abstract
Recent scholars of Pre-Raphaelite art have focused on the history of women, material culture, and social context. An area that has received little attention is the concept of nationalism and national identity. This thesis closely examines the influence of such ideas through paintings created by Dante Gabriel Rossetti, John Everett Millais, and William Holman Hunt, between 1848 and 1865. To outline these directions, artist biography, correspondence, and the nineteenth-century British press were considered critically. What this study reveals is that Pre-Raphaelite art was heavily influenced by socio-political, national and international events. Previously, Rossetti, Millais, and Hunt were understood to be rebellious, anti-establishment artists; this study shows that these artists were aware of their shifting political and cultural atmosphere, and consciously catered to national sentiment in order to gain financial success. Early paintings of Rossetti, Millais, and Hunt coincide with the religious, evangelical fervour of the mid-nineteenth century. I argue that Rossetti continued to appeal to religious buyers through a Cycle of Mary images in the 1850s and was influenced by the Morant Bay Rebellion (1865) in his creation of The Beloved (1865, Tate). In the early 1850s, Millais appealed to popular opinion in his works through commentary on the Protestant-Catholic debates, and the Crimean War (1853-56). Through their correspondence, we now know that Millais and Rossetti did not share the views represented in their art, which further highlights the financial motivations behind the paintings. Furthermore, I argue that the early reviews of Pre-Raphaelite paintings were affected by the national religious mood, and coincidentally by the Irish Potato Famine (1845-52). A study of the press reveals stark similarities in language between these reviews and the debates on national and international events. Unlike Rossetti and Millais, Hunt relied on his personal beliefs to create his early religious paintings. However, I argue that to attract specific buyers such as Thomas Combe and Ernest Gambart, Hunt modelled his paintings after popular evangelical sermons. Through the lens of nationalism, this study offers a new perspective which can help unify the often-fragmented study of Pre-Raphaelite art, and make it relevant across multiple disciplines.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".