A New Historicist Perspective of Thomas Preston’s Cambyses: A Lamentable Tragedy Mixed Full of Pleasant Mirth
Bibliographic record
Abstract
This paper aims at the application of new historicist principles to Preston’s Cambyses. It begins with the elaboration of the key assumptions of new historicism. Particularly, the researchers have applied the new historicist concepts such as use of anecdote, historicity of text and textuality of history, discourse and power relations and construction of identity for the purpose of detailed analysis of the play. The available traditional criticism focuses on the topical and political interpretations of the play. The paper evinces a departure from traditional criticism since the researchers contend that Preston has used the literary discourse of Cambyses as an ideological tool to propagate and promote the idea of British Empire and thereby helped fashion the identities of his audience. The play functions as a part of continuum in representing Persians as cultural others with other historical and cultural texts of early modern period. Through the story of a cultural other like Cambyses, the play not only instructs and entertains his audience but also tends to support the dominant ideology of the period. The research findings confirm our contention that the Western playwrights like Preston have deliberately chosen the story to disseminate the idea of British Empire that developed later on but its foundations were laid down in the early modern period.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.031 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| 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".