A Comparative Analysis of Violence in A Rose for Emily and in Lord of the Flies
Bibliographic record
Abstract
A Rose for Emily and Lord of the Flies , as the respective masterpiece of Faulkner’s and Golding’s, have long been studied by scholars in different times, but seldom discussed and compared violence in them before. In order to make an all-around exploration of violence in literary works, this paper conducts a comparative study on violence in these two novels from five perspectives: social background, manifesting form of violence, criminal behaviors, violence types and pursuits of protagonists. These two novels share similarities and differences on violence. As for similarities, both novels are under depressive social background, with similar manifesting forms of violence. In addition, both protagonists kill others to fulfill their own desires. As for differences, A Rose for Emily tells about women violence, while Lord of the Flies talks about men violence. Besides, in the former novel, Emily is in the pursuit of love and self-awakening, while in the latter novel Jack pursues power. Through comparison, this paper reveals that violence is rooted from desire for unattainable love or goals and the evil side of human nature. Therefore, it is necessary for readers to pay attention to cultural, social, political and psychological factors behind violence aesthetics in literature and then reduce realistic violence.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.010 | 0.012 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".