Why this work is in the frame
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Bibliographic record
Abstract
Based on the analysis of the three selected North American novels -Dionne Brand 's Toronto, What We All Long For (2005), Chang-rae Lee's New York, Native Speaker (1995), and Karen Tei Yamashita's Los Angeles, Tropic of Orange (1997) -this work examined global cities as a literary phenomenon ('diverCity').As shown, the poetics of narrative, place, and code-switching function as the common aesthetics of global, urban, and ethnic literature.Thus, this structured analysis of a poetics of 'diverCity' provided the connecting link for examining the triad of globalization and its effects, global cities as cultural nodal points, and cultural diversity in a globalizing age as a literary phenomenon.In this work, the analysis by a poetics of diverCity provides the opportunity to illustrate how the common aesthetics are of significance to each of the three selected novels.The poetics of narrative, place, and code-switching are important in Tropic of Orange (1997) when portraying the cultural multiplicity, urban-geographic complexity, and socio-political ruptures of the global city.Although, both the poetics of place and narrative are essential in Native Speaker (1995), the poetics of code-switching is the novel's dominating strategy in visualizing, exploring, and translating urban immigrant life and the integration of different ethnic groups into urban society.Similarly, with the poetics of narrative and code-switching, What We All Long For (2005) illustrates the different coexisting and overlapping worlds within the city while focusing its exemplifications on concepts of urban place and space.The three poetics thus play an important, albeit different, role in each literary analysis.In this study, the poetics of narrative mainly concentrates on the novel's genre, intertextuality, and narrative voice.In Native Speaker (1995), for example, different genre conventions, such as the immigrant novel, the spy thriller, and the detective story, are combined to maneuver outside literary and cultural categories.In Tropic of Orange (1997), the story of Christopher Columbus' conquest
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.020 | 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 it