“The boundary has been moved”: Hollywood cinéma-monde, film borders, and the multilingual assassin in <i>Sicario</i> and <i>Inglourious Basterds</i>
Bibliographic record
Abstract
Transnational coproductions, multilingual dialogue, and border-crossing of many forms are growing increasingly common in contemporary cinemas. As a result, assigning a nationality to a film can prove a slippery and even arbitrary process. This article takes a new approach to films such as Sicario (Denis Villeneuve 2015) and Inglourious Basterds (Quentin Tarantino 2009), analyzing texts traditionally viewed as American through the lens of cinéma-monde (Marshall 2012). It focuses in particular on these films’ use of maps, and on their strikingly similar multilingual assassination scenes, reading them through Bill Marshall’s characterization of a cinema that “dramatically focuses attention on four elements: borders, movement, language, and lateral connections” (42). Each of these films was directed by an established auteur working in a “foreign” space and non-native languages, and each depicts continual border-crossing, code-switching, and violence committed across geographic and linguistic lines. With significant American and other characteristics, neither Sicario nor Inglourious Basterds could be neatly categorized as Quebecois nor French respectively. Yet these films implicate the French-speaking world in diverse ways. Ultimately, the ways in which these films traverse, theorize, and weaponize the border begs a questioning of how far the concepts of national cinemas, and indeed of cinéma-monde, can be extended.
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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 | 0.009 | 0.010 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".