Bibliographic record
Abstract
In the contemporary time, the Chinese cinema has seen the emergence of various cinematic strategies in representing filmic cities. Among the sixth-generation directors, the topophilia strategy is most frequently discussed. However, Diao Yi'nan, an often neglected sixth generation director, emerges to the spotlight with his ground-breaking crime drama, Black Coal, Thin Ice and continues to gain attention ever since. Differing from the typical topophilia approach, Diao adopts distinct cinematic strategies to explore the intersection of individual sentiments and urban spaces. This essay builds itself on past research to analyze these strategic differences. The key theory adopted is the "emotional cartography", a psychogeography concept that explores the intersection of spatiality and subjectivity. Viewing filmic city as an "emotionally heightened space", the emotional cartography allows for the unveiling of hidden social relations as mediated by feelings and sensibility in a specific spatial system. The anxiety of living in a fleeting material world and changing social relation could be thus seen as the implicit political message hidden in Diaos narrative. The second part is built on past research and analyzes the narrative force of Diao Yi'nan's film. Affirming the logic of "atypical affects" () proposed by Qi Wei, the second part argues that the logic of atypical affects is also the underlying force for Diao's emotional cartography. Last but least, the essay argues for Diao's use of surrealism adheres to the logic of affects and externalize characters' psychologies.
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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 | 0.004 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".