“Worthy my blood”: Inheritance, Imitation, and Gendered Familial Emotions in John Marston’s <i>Antonio</i> Plays
Bibliographic record
Abstract
Examining the Antonio plays by John Marston, I argue that the metaphors used to portray familial emotions reveal the ideologies that underpin both excessive and normative versions of familial relationships; these metaphors reveal the pressures placed on family emotions by economic and political ideologies. While critics have traditionally read instances of family breakdown in plays as moments that violate kinship norms, I argue that such moments of violence are caused by ideologies associated with inheritance structures which underpin descriptions and experiences of normative familial emotions. A travers l’examen des pièces de théâtre d’Antonio de John Marston, je soutiens que les métaphores employées pour représenter les émotions familiales font apparaître les idéologies qui sous-tendent tant des versions excessives que des modèles normatifs pour lees relations familiales. Ces métaphores révèlent la pression que font subir aux émotions familiales les systèmes de pensée économiques et politiques. Alors que les critiques ont traditionnellement lu les exemples d’éclatement familial dans le théâtre comme des moments violant les normes de la parenté, je soutiens que de tels moments de violence sont causés par des systèmes associés aux structures d’héritage qui sous-tendent les descriptions et les expériences des émotions familiales normatives.
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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 | 0.000 |
| Science and technology studies | 0.009 | 0.022 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 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".