Bibliographic record
Abstract
In Sir Gawain and the Green Knight, the question of late medieval heroism is a central one. Morton Bloomfield, for instance, has argued that “The drastic ambiguity of the hero in the later Middle Ages is perfectly revealed in Gawain and the Green Knight where the problem of the hero becomes acute.” Like other romance protagonists, Gawain displays great martial courage. He accepts the Green Knight’s challenge, battles his way through a perilous forest, and jumps to fight the Green Knight as soon as he realizes that the latter has not beheaded him. However, Gawain’s opportunities to prove himself in battle are far outnumbered by the humiliations that he suffers during his adventure. Camelot’s code of conduct compels him to accept the Green Knight’s challenge, the narrative quickly summarizes his martial accomplishments in the forest, and the Green Knight responds with slight amusement to Gawain’s aggressive challenge after the young knight must submit to a third feint of his opponent’s axe. Furthermore, Gawain discovers that he has been the victim of an elaborate plot to humiliate Camelot and comesto realize that his acceptance of Lady Bertilak’s girdle has been an act of cowardice. In spite of these factors which would seem to diminish his heroism, the Green Knight refers to Gawain as “On þefautlest freke þat euer on fote Šede” (2363).
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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".