Struggle in Pain and Desperation: an Analysis of the Tragic Image of Willy Loman in Death of a Salesman
Bibliographic record
Abstract
Arthur Miller was one of the most famous playwrights after Eugene O’Neil in modern America. His masterpiece Death of a Salesman successfully characterized a tragic image——Willy Loman. His tragedy is not only personal, but also the tragedy of family relationship and American dream. Key words: Death of a Salesman, tragic image, American dream Resume Arthur Miller est l’un des plus connus dramaturges apres Eugene O’Neil dans la scene dramatique americaine. Il campe avec succes le personnage tragique Willy Loman dans son chef-d’oeuvre Mort d’un commis-voyageur. La tragedie de Willy Loman n’est pas seulement une tragedie personnelle, mais egalement la tragedie de la relation familiale et celle du reve americain. Mots cles : Mort d’un commis-voyageur, l’image tragique, le reve americain 摘 要 亞瑟•米勒是當代美國劇壇繼奧尼爾之後最著名的劇作家之一。他在其代表作《推銷員之死》中成功地塑造了威利•洛曼這一悲劇形象。威利 •洛曼的命運悲劇不僅是其個人的悲劇 ,也是家庭關係的悲劇 ,更是美國夢的悲劇。 關鍵詞：《推銷員之死》；悲劇形象；美國夢
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.009 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".