Revisionary Historical Metatext or 'Good Mills and Boon'?: Gender, Genre, and Philippa Gregory's The Other Boleyn Girl
Bibliographic record
Abstract
In recent decades, literary critics have become increasingly interested in the ways that contemporary historical novels are used to write “history from below.” In On Lies, Secrets, and Silence (1978), Adrienne Rich describes a process she calls “re-visioning,” a process that is defined as “looking back, of seeing with fresh eyes, of entering an old text from a new critical direction” (35). Many female authors of contemporary historical novels engage in exactly this process, looking back in time and reinserting the histories of women into the dominant narrative of history in which they are often excluded or marginalized. Novelists like Philippa Gregory, Diana Gabaldon, and Tracy Chevalier have made feminist politics clearly visible in their bestselling historical novels. And yet, for all their potential and visible disruptions of patriarchal ideology, many of these popular novels also make use of literary archetypes, tropes, and narrative patterns that reinstate hegemonic ideologies about individual identity and social structure. Using Philippa Gregory’s The Other Boleyn Girl (2001) as a case study, this paper argues that popular women’s historical novels often exist in tension between the pulls of revisionary feminist historiography and the popular romance narrative.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.024 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".