Novels study of Du Xiu Lan
Bibliographic record
Abstract
[[abstract]]杜修蘭自1996至2003年為止，先後發表了《逆女》、《別在生日時哭泣》、《默》、《沃野之鹿》、《溫哥華的月亮》五部中長篇小說。《逆女》為作者第一部小說，發表後即獲得第一屆皇冠百萬小說首獎，並改拍成電視劇，在金鐘獎上大放異彩，《默》亦獲得第十九屆聯合報文學獎長篇小說獎，《沃野之鹿》中觸及的原住民題材書寫，成為許多學者研究的材料，另外兩部作品《別在生日時哭泣》與《溫哥華的月亮》中的成長議題亦發人省思。筆者觀察其小說書寫特色，發現杜修蘭在小說的經營上有其獨到之處。本文聚焦於杜修蘭在小說中「人物設置」、「主題呈現」、「書寫策略」等三個面向作分析、整理，最後以杜修蘭作品中的人物塑造技巧對小說營造的功能、對讀者產生的影響與所欲傳達的社會關懷作結。 Du Xiu Lan has published middle and full-length novels, such as Unfilial Daughter, Do Not Cry on Birthday, Silence, The Deer of Fertile Land and The Moon in Vancouver from 1996 to 2003. Unfilial Daughter is the first novel of the author. After publishing, Unfilial Daughter won the first prize of the first Million Novel Crown and was filmed as TV series. Furthermore, Unfilial Daughter showed extraordinary results on the Golden Bell Awards. Also, Silence obtained the novel prize for nineteenth literature prize of United Daily News. Moreover, The Deer of Fertile Land can be the resource of many scholars because the content of The Deer of Fertile Land talks about aboriginal. Besides, the other works, Do Not Cry on Birthday, Silence and The Moon in Vancouver discuss the growing events that can provoke people to do deep thinking. The writer observes the writing styles of those novels, then discovers that Du Xiu Lan utilizes unique way in novel arrangement. The article focus on the analysis and characteristics of three aspects in Du Xiu Lan’s novels: 1. Character setting, 2.Theme presenting and 3. Writing strategies. Finally, the article was concluded by discussing the function of novel arrangement, readers influence and social caring from the techniques of character creation in Du Xiu Lan’s works.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".