Reading Lovelace’s “Rosebud”: Credits, Debits, and Character in Samuel Richardson’s <i>Clarissa</i>
Bibliographic record
Abstract
Early in Samuel Richardson’s Clarissa (1748), Lovelace boasts of not raping a seventeen-year-old whom he identifies as “his Rosebud.” While critical references to Rosebud are now rare, her presence preoccupied early readers who were so impressed by Lovelace’s generosity that they could scarce believe his later actions toward Clarissa. Although Lovelace acknowledges that years of criminal behaviour have destroyed his reputation, he nevertheless fantasizes that such “generosity” might establish an economy of credits and debits whereby one non-rape can count against a future sexual assault. While Lovelace’s fantasy fails on multiple levels—he invokes the logic of double-entry bookkeeping only to misunderstand it, and his non-rape of Rosebud is, of course, not actually generous at all—it offers a paradigm for understanding Richardson’s broader approach to character. As even Lovelace recognizes, not raping Rosebud can never render him innocent in a larger sense. Returning to Rosebud allows us to read Clarissa as a novel in which character remains fixed, even if it takes hundreds of pages to fully unfold.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".