Literary and cultural (re)productions of a utopian island: Performative geographies of colonial Shamian, Guangzhou in the latter half of the 19th century
Bibliographic record
Abstract
: In the second half of the 19th century, Shamian was established and developed as a colonial island enclave in the Chinese city of Guangzhou. Simultaneously, literary and cultural imaginations, depictions, and narrations of the place produced a discourse of Shamian as a utopian island: geographically insular and bounded, environmentally beautiful and peaceful, socially exclusive and harmonious, and technologically progressive and advantageous. This paper examines contemporaneous (predominantly English) literary and cultural representations of Shamian as a colonial utopia and their interrelations with the island’s spatial formation and evolution. These texts (primarily written and pictorial descriptive, nonfictional accounts) reflected the spatial reality but also promoted spatial practices that reinforced the physical utopian island. This process exemplifies the theories of performative geographies in island studies and intertextuality in geocriticism, showing how a place’s spatial representations and reality are mutually constructed. Adopting a conceptual model of intertextual performative geographies, this paper investigates the dynamic interplay of these literary and cultural texts with the spatial reality, arguing that literary and cultural representations of Shamian (re)produced the colonial enclave as a utopian island, both conceptually and practically.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".