The Interweaving of Chineseness, Localness, and Modernity: The Construction of Sinophone Subjectivity in Li Zishu’s Worldly Land
Bibliographic record
Abstract
Malaysian Chinese (Mahua) literature occupies a unique position at the intersection of Chineseness, Localness, and Modernity, forming a three-dimensional framework of cultural hybridity. However, despite this inherent richness, Mahua literature has long grappled with the predicament of an “absence of classics,” as many writers struggle to integrate these dimensions cohesively. Using Li Zishu’s Worldly Land (2021) as a case study, this study explores how narrative strategies can serve as cultural mechanisms for constructing sinophone subjectivity. Employing Gérard Genette’s narratological model, the analysis focuses on three core aspects - narrative tense, mood, and voice - to uncover how the novel orchestrates complex cultural synthesis. The findings reveal that Chineseness is primarily conveyed through narrative mood, particularly via the use of direct speech and omniscient storyteller-style focalization rooted in Ming-Qing vernacular fiction. Localness is manifested across all three narratological dimensions through repeating narrative, multicultural dialogue, and shifts in narrative perspective, whereas modernity emerges through free direct speech and the destabilization of linear temporality. By demonstrating how Worldly Land (2021) weaves these three dimensions into a cohesive narrative, this study not only provides a model for future Mahua literary creation, but also offers new insights into how cultural hybridity and identity negotiation are articulated through narrative form within the global Sinophone literary framework.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".