Bibliographic record
Abstract
In this article, I assess Philippe Grandrieux’s Un lac (2008) through the lens of the sublime. I offer a formal analysis of the film supported by contemporary theorists who have previously articulated the stakes of Grandrieux’s work in the tradition of narrative cinema. Similar to prior research, my work sets out to understand Grandrieux’s aesthetics and how his filmmaking attempts to engage spectators’ sensory engagements and alter their perceptions of film. Where I diverge is in demonstrating how the theory of the sublime is useful for theoretical understandings of Grandrieux’s films and experimentations with narrative cinema more generally. Specifically, I turn to Un lac’s protagonist Alexi as an anchor to unpack Grandrieux’s experimental cinematography, editing, and sound. Following this, I examine the film through Cynthia A. Freeland’s conceptualization of sublime cinema. I conclude that the snowy landscapes, overwhelming woods, treacherous weather, and fragile bodies in the film work to diminish and dismantle the human figure. I draw on recent theories of cinema and affect to argue that the sublime encourages us to rethink our ontological presuppositions – Un lac posits an alternative to anthropocentrism.
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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 | 0.004 |
| 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 | 0.012 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".