The Impact of Culture Differences on Film --Taking Farewell My Concubine as an Example
Bibliographic record
Abstract
Almost all of Chen Kaige’s works, such as the film Farewell My Concubine, include a significant historical and cultural theme to express his views and understanding of traditional culture and human nature. The film illustrates the ups and downs of Peking Opera performers’ lives in the context of a tumultuous society, with the art of Peking Opera serving as a point of reflection. Farewell My Concubine, as an epic work of cinema, is unusually rich in the use of cinematic symbolism and aesthetics, which not only adds to the film’s vivid connotation but also inspires people to think profoundly. A huge variety of realistic metaphors hide the character and fate of the film’s three major protagonists under rich cinematic symbols and aesthetics. As an important medium for cultural transmission, the film is a popular choice for cultural imports from other countries. This paper investigates the influences of cultural variations on viewers’ understanding of film in the context of cultural diversity, as well as the reasons for this impact and the techniques available to overcome it, so as to offer some references for future researches.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".