‘Come with me, sweetest sister’: Unravelling the Enigma of Sacred Sisterhood in Aurora Leigh by Elizabeth Barrett Browning and “Goblin Market” by Christina Rossetti
Bibliographic record
Abstract
Throughout the Victorian era, Elizabeth Barrett Browning and Christina Rossetti occupied a prominent position in a newly emerging female literary movement. Both authors sought to resist and revise the limitations of Victorian womanhood through the composition of controversial works that rivalled the achievements of their male contemporaries. In the 1856 epic Aurora Leigh by Elizabeth Barrett Browning and the 1862 narrative poem “Goblin Market” by Christina Rossetti, both Barrett Browning and Rossetti employ an early feminist perspective to explore the parameters of Victorian sisterhood and the potential strength of female friendship. Although Laura, Lizzie and Jeanie in Rossetti’s work possess a sororal relationship that is distinct from Marian Erle and Aurora Leigh’s relationship in Barrett Browning’s work, the innumerable connections between both publications have caused critics to compare and hierarchize the two authors. Thus, a literary sisterhood has developed between Barrett Browning and Rossetti that curiously mirrors the sisterhoods of their fictions. This paper seeks to assess the inescapable presence of sisterhood in Aurora Leigh and “Goblin Market” by analyzing the manner in which a sisterly connection, not only through blood relations but also through close friendships that resemble sisterhood, allowed female forces to be allied, nurtured, and empowered amidst the patriarchal and misogynist structures of mid-nineteenth century Britain.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.027 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".