Banished Bodies and Spectral Identities: The Aging Actress in William Hazlitt’s Retirement Essays
Bibliographic record
Abstract
This article argues that eighteenth-century theatrical reviews and biographical descriptions equate the physical decline of the aging actress with the loss of her identity. It analyses disappearing selfhood through an investigation of the intersection of gender and age in William Hazlitt’s essays on retiring players: namely, “Miss O’Neill’s Retirement,” “Mr. Kemble’s Retirement,” and “Mrs. Siddons’ Lady Macbeth.” In these essays, Hazlitt suggests that the actress only maintains her public identity through an early departure from the stage. This is enforced by societal understandings of normative and desirable femininity as youthful. To emphasize the feminine loss that accompanied aging, Hazlitt and his contemporaries would often juxtapose a player’s physical body with those of younger players, as well as with the memory—or ghost—of its own younger form.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.016 | 0.022 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".