Bibliographic record
Abstract
Many of Ingmar Bergman’s films are indebted to the horror genre through topics that explore physical and psychological torture, mutilation, illness, murder, sexual taboos, dream, psychoanalysis, madness, and the supernatural. These emblematic horror tropes are reinforced with close-ups of expressive mouths and eyes and a masterful manipulation of shadow and light, helping to create an aesthetic that is at once intimate and haunting. There is a third plane, an aural one, on which Bergman intertwines music, a rich palette of sound effects, deathly silence, and blood-chilling screams. This paper focuses on the significance of music and the voice (or the lack thereof) in Bergman’s soundtracks and expands ideas put forward by Julia Kristeva about the “abject” and by Michel Chion pertaining to the omniscient and bodiless acousmêtres or “acoustical beings” and mutes of film. This article examines mutes and acousmêtres in Persona and Hour of the Wolf, and how the quality of their voices or, indeed, their silence, aids them in articulating their identities and manipulating and tyrannizing those around them. Bergman’s characters threaten to destabilize the narrative if and when they find their bodies and/or voices, and thus maintain an ominous power as they straddle diegetic and non-diegetic aural space.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".