Bibliographic record
Abstract
The one-shot sequence – the articulation of an entire scene through a single, unbroken long take – is one of the cinema’s most important rhetorical devices and has therefore been much used and widely theorised over the years. This article provides a brief overview of these theories and of the multiple ways in which the one-shot sequence has been used both in world cinema (in general) and Italian cinema (in particular) in order to contextualise its use by one of Italian cinema’s best-known and most significant practitioners, Paolo Sorrentino. Through close analyses of one-shot sequences in Sorrentino’s films L’uomo in più/One Man Up, Le conseguenze dell’amore/The Consequences of Love, This Is the Place and Il divo – La vita spettacoloare di Giulio Andreotti – the article argues that Sorrentino’s predilection for the device is best explained by the wide variety of functions that it serves (as a mark of directorial bravura and auteur status; as a self-reflexive device and meditation on the cinematic gaze; as a political tool; and as a means of generating emotion). While rooted in history, Sorrentino’s use of the one-shot sequence thus transcends its position within Italian film history and discourse.
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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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.080 | 0.064 |
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".