Bibliographic record
Abstract
The repetition of a story at a particular moment in time – in the case of this book, the story of seduction in the later half of the eighteenth century in Britain – prompts at least two different interpretations of how history relates to narrative. The same story might be repeatedly told in order to popularize and naturalize a new historical idea, foregrounding a relation of similitude and emphasizing the mimetic or didactic function of narrative. Or the repetition of a story could denote difference where the deviations within similarity point to a dynamic relation between material conditions and imaginative narratives; in this case, the fact of a story's repetition would indicate both that changing historical conditions open up new objects of understanding and that narrative helps to constitute and to resolve conflicts posed by those new objects. The Seduction Narrative assumes the second formulation to explain how history and narrative interact in the “later eighteenth-century's preoccupation with seduction,” as one historian names the obsessive retelling of the tale. The plot of seduction – where a virtuous young heroine is seduced into believing her lover's vows – dramatizes women's consent to sex at a historical moment when, for the first time, women have “a right to a heart,” as Clarissa boldly claims. The period in Britain under study (1747–1800) witnesses the emergence of companionate marriage as a dominant cultural ideal and this revolution in the history of love carries with it a new social and cultural imperative for women to know their hearts and make choices based upon those affective truths.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.625 | 0.445 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".