The Problem of Revenge in Medieval Literature: Beowulf, The Canterbury Tales, and Ljósvetninga Saga
Bibliographic record
Abstract
This dissertation considers the literary treatment of revenge in medieval England and Iceland. Vengeance and feud were an essential part of these cultures; far from the reckless, impulsive action that the word conjures up in modern minds, revenge was considered both a right and a duty and was legislated and regulated by social norms. It was an important tool for obtaining justice and protecting property, family, and reputation. Accordingly, many medieval literary works seem to accept revenge without question. Many, however, evince a great sensitivity to the ambiguities and paradoxes inherent in an act of revenge. In my study, I consider three works that are emblematic of this responsiveness to and indeed, anxiety about revenge. Chapter one focuses on the Old English poem Beowulf; chapter two moves on to discuss Chaucer’s Reeve’s Tale and Tale of Melibee from the Canterbury Tales; and chapter three examines the Old Icelandic family saga, Ljósvetninga saga. I focus in particular on the treatment of the avenger in each work. The poet or author of each work acknowledges the perspective of the avenger by allowing him to express his motivations, desires, and justifications for revenge in direct speech. Alongside this acknowledgement, however, is the author’s own reflection on the risks, rewards, and repercussions of the avenger’s intentions and actions. The resulting parallel but divergent narratives highlight the multiplicity of viewpoints found in any act of revenge or feud and reveal a fundamental ambivalence about the value, morality, and necessity of revenge. Each of the works I consider resists easy conclusions about revenge in its own context and remains incredibly current in the way it poses challenging questions about what constitutes injury, punishment, justice, and revenge in our own time.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.019 | 0.044 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.004 |
| 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".