Comparing Film Language Amongst Genres: A Comparative Analysis of Schindler's List, In Darkness and The Last Days
Bibliographic record
Abstract
The purpose of this paper is to provide a comparative analysis of the film language and genre conventions used in three Holocaust films, Schindler's List, In Darkness and The Last Days. Each of these films provide the perspective of a unique genre on real historical people and events that took place during the Holocaust. Schindler's List is a biopic film that follows the true story of Oskar Schindler, a wealthy German businessman who managed to save the lives of more than 1,000 Jews by keeping them employed in his factory during the Holocaust. In Darkness is a Polish-made drama film which profiles Leopold Socha and the 10 Jews he managed to save by helping them to hide in the sewers during the Holocaust. The men profiled in both movies were declared Righteous Among Nations for their heroic real life actions. The final film, The Last Days is a documentary, which profiles the stories of survival of five Hungarian-Jews during the Holocaust. Through the use of film language, Schindler's List, In Darkness and The Last Days are all able to effectively communicate key themes and ideas present during the Holocaust. Symbolism is used in each of these films in the areas of colour and light. This symbolism, most heavily present in Schindler's List, seems to depict the lack of light, or lack of hope during the Holocaust. Another theme present in the films is the stark inequality between Germans, common people and Jews. This inequality is particularly relevant to both Schindler's List and The Last Days. All three films effectively capture the emotion of their audiences by making them feel as if they are actually experiencing the Holocaust through the use of both camera movement and real footage. A final important idea surrounding this Holocaust that can be taken away from each of these films is the brutality of German soldiers. Overall, the analysis of these three films provides a powerful and personalized insight into the Holocaust.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".