Marshall, Kingsley. 2020. ‘Allied: Zemeckis and Silvestri. Longstanding Relationships Between Composers and Directors’. In Barkman, Adam and Sanna, Antonio (Eds.). 2020. A Critical Companion to Robert Zemeckis. Lanham, US: Lexington Books
Bibliographic record
Abstract
“I'm standing there in this Calvin Klein white sweater, and all of a sudden Bob walks in wearing the exact same sweater. Right then, we knew that we were connected for life" (Silvestri, 1995). The collaboration between composer Alan Silvestri and director Robert Zemeckis began with Romancing the Stone (Zemeckis, 1984) and has continued through to the present day, with their eighteenth collaboration The Witches due in cinemas 2020. In order to better understand the relationship between Silvestri and Zemeckis, this chapter draws an alignment of the creative practice of these film with a detailed, intrasoundtrack analysis of the scenes they discuss. I will make use of interviews to explore their working relationship and use these to contextualise the close reading of specific scenes selected from four live action films of their relationship – including Flight (2012), The Walk (2015), Allied (2016) and Welcome to Marwen (2018). These four recent films have been chosen as they represent the well-developed relationship between composer and director, and each articulate genre, space, place and character subjectivity in a complex manner through the combination of musical and moving image Vicki Mayer observes that this analysis of cultures of production, when applied to specific productions, speaks not just to the film under examination, but can offer “larger lessons about workers, their practices, and the role of their labors in relation to politics, economics and culture” (2009: 15). I argue that such longstanding collaborative relationships, and a practice of involving music composers within the development stages at the initiation of film projects, can serve to privilege sound more broadly within a film and commonly results in a greater integration of music within the films themselves than is common in film production. Amy McGill argues that a “contemporary” narrative mode of sound and music within cinematic storytelling emerges in the 1970s (2008), a development of film sound born of “the industrial realignments that led to flexible production processes, technological developments and emerging trends in storytelling technique and generic style, all of which have contributed to the diverse and complex character of the contemporary soundtrack” (2009: 289). Silvestri’s work with Zemeckis over a thirty-year period offers an opportunity to consider the manner with which this mode manifests itself in their work, and offer commentary on the manner with which this use of sound can be sound to demonstrate the blurring of distinctions between international art cinema, American independent filmmaking and US studio productions occurring during that period (2008: 293-294).
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.093 | 0.024 |
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".