Film sound and American cultural memory: Resounding trauma in <i>Sophie’s Choice</i>
Bibliographic record
Abstract
One of the most dynamic discussions in memory studies concerns memory’s infusion with phantasy, which Freud also referred to as fantasy. This article examines how memory and fantasy intermingle in ways analogous to the ambivalent human experience of sound: sounds and musical cues can both trigger memories and be active in repressing them by encoding them into fantasmatic ‘counter memories’. Taking Alan J. Pakula’s film Sophie’s Choice (1982) as a case study, I examine how the three principal characters are traumatized by intruding sounds, but use music to repress or reconfigure the memories these sounds trigger. Sophie’s memories of Auschwitz are signalled by Hamlisch’s flute, which provides the soundscape of her fantasy-infused flashbacks; her companion Nathan’s delusional ‘memories’ of the war are safely repressed when the oboe supplies him with his ego’s anthem; and sounds from the narrator Stingo’s childhood rupture the nostalgic soundtrack of violins accompanying his fantasy-inflected narrative. The relevance of Pakula’s melodrama to the social memory of the Holocaust lies in its challenge to the polarized debate between modernist refusals to represent the past ‘directly’ (as in Claude Lanzmann’s 1985 film Shoah) and realist attempts at ‘total representation’ (Steven Spielberg’s 1993 film Schindler’s List). In Sophie’s Choice, acts of individual memory, infused with fantasy soundscapes, are analogous to broader processes of social memory, which are always instilled with our fantasies of what might have been.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".