Behind Idealism: The Discrepancy between Philosophy and Reality in The Cinema of Lars von Trier
Bibliographic record
Abstract
ABSTRACT: “All my life I’ve been interested in the discrepancy between philosophy and reality, between conviction and its implementation.” (Lars von Trier, 2005) Most scholarly attention has so far been directed towards the elements of form and cinematography in Lars von Trier’s work. In this paper I will instead focus on the thematic and philosophical qualities of his work. Through analysis of protagonist types and plot structures, I will show how “the discrepancy between philosophy and reality” functions as a central underlying structure in the films. But also how this discrepancy shifts according to gender and over time in von Trier’s later production. I will also examine von Trier’s ties to nineteenth-century Scandinavian drama and German philosopher Friedrich Nietzsche. These are important connections which have as yet not received the attention they deserve.
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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) | 0.000 | 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) | 0.000 | 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".