Serialized Identities and the Novelistic Character in Eliza Haywood’s <i>Fantomina</i> and <i>Anti-Pamela</i>
Bibliographic record
Abstract
Eliza Haywood’s Fantomina (1725) and Anti-Pamela (1741) document an increasing social disapprobation for identity play within novels and a return to an understanding of class identity as an innate attribute. Applying Mary Jo Kietzman’s theories of serial subjectivity to Haywood’s novels brings into view the conflict between two different modes of identity construction in the mid-eighteenth century: identity as a matter of performance, and identity—particularly status—as fixed. Haywood departs from tradition by limiting her serial subjects, indicating an emerging social censure of this figure. The upward social mobility attempted by these protean characters appears to be their most objectionable quality, and as such these figures rehearse and respond to the problems at the centre of the Pamela controversy (1740). Haywood’s texts and their engagement in this debate allow us to better conceptualize the intersections between identity and status, and narration and plot, that were central to the development of the early novel.
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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 | 0.002 | 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 | 0.007 | 0.023 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".