Dramatic Autobiography: the Poetic Voice Recreating Itself in Dante Gabriel Rossetti’s ‘The Bride’s Prelude’
Bibliographic record
Abstract
The dramatic monologue is one of the most important of the new Victorian poetic forms, and was designed to decipher the soul and probe into it, with the objective, to quote Browning’s dedication to John Milsand in his poem ‘Sordello’, to lay stress on ‘the incidents in the developments of the soul’. As such, this poetic form helps recreate a life, through the fictitious reality of the poetic voice: by talking about itself and primarily to itself, the poetic persona of the dramatic monologue builds up an imaginary autobiography. Some of Dante Gabriel Rossetti’s poems which can qualify as dramatic monologues use this fictitious autobiography to give a voice to marginalized populations, for instance ‘The Bride’s Prelude’. This poem presents a woman about to be forcefully married to a man who deceived her and abandoned her, as she explains to her sister why she cannot look forward to this marriage. Her explanation of what happened constitutes a dramatic autobiography, or an autobiographical monologue: a genre at the crossroads between autobiography and dramatic monologue, in which a voice which is rarely heard is given the opportunity to tell its own version of the story. This recreation of a life story gives the artist the opportunity not only to paint a vivid picture of a time long gone, but to question mechanisms of power in a way that might resonate in Victorian times. For an author such as Rossetti, who stayed clear of politics most of his life, fake autobiographies might be seen as a way to engage with contemporary issues, through the prism of someone else’s life and borrowed autobiographical voices.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".