Bibliographic record
Abstract
In a recent article, ‘Heywood, Henslowe and Hercules: Tracking 1 and 2 Hercules in Heywood's Silver and Brazen Ages ’ ( EMLS , 17.1, 2014), I argued that the two Hercules plays performed by the Admiral's Men in 1595-96 were by Heywood and were adapted by him into the Silver and Brazen Ages . If this argument is valid, it makes it very likely that Heywood also wrote the Troye mentioned in Henslowe's Diary as performed in 1596 and that he later adapted it into 1 and 2 The Iron Age . In the medieval version of Greek mythology, the Trojan War follows closely on the Hercules story. Heywood’s long poem Troia Britanica can be used as a guide to determining the material added to Troye to create the Iron Age plays. There are many signs that the parts of the Iron Age plays that I propose approximate the original Troye were written in the mid-1590s. The most notable of these is the fact that they influenced Shakespeare’s Troilus and Cressida , written c. 1601. While contemporary scholars have suggested that Heywood was influenced by Shakespeare in writing 1 The Iron Age , I present reasons for believing that the influence went the other way. Recognizing that Shakespeare got much of his Homer from Heywood adds to the doubts expressed by some scholars that Shakespeare used The Iliad as a source.
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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 | 0.015 | 0.036 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".