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Record W4205739655 · doi:10.26881/pan.2021.26.04

Loop Structures in Film (and Literature): Experiments with Time Between the Poles of Classical and Complex Narration

2021· article· en· W4205739655 on OpenAlexaboutno aff
Matthias Brütsch

Bibliographic record

VenuePanoptikum · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicNarrative Theory and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsNarrativeJudgementMainstreamStorytellingHistoryNarrative structureLinguisticsMedia studiesSociologyLiteraturePolitical scienceLawArtPhilosophy

Abstract

fetched live from OpenAlex

Among the many innovations complex or “puzzle” films have brought about in the last three decades, experiments with narrative time feature prominently. And within the category of nonlinear plots, the loop structure – exemplified by films such as Repeaters (Canada 2010), Source Code (USA/France 2011), Looper (USA/China 2012) or the TV-Series Day Break (USA 2006) – has established itself as an interesting variant defying certain norms of storytelling while at the same time conforming in most cases to the needs of genre and mass audience comprehension. In the first part of my paper, I will map out different kinds of repeated action plots, paying special attention to constraints and potentialities pertaining to this particular form. In the second part, I will address the issue of narrative complexity, showing that loop films cover a wide range from “excessively obvious” mainstream (e.g. Groundhog Day, USA 1992; 12:01, USA 1993; Edge of Tomorrow, USA/Canada 2014) to disturbing narrative experiments such as Los Cronocrimenes (Spain 2007) or Triangle (Great Britain/Australia 2009). Finally, a look at two early examples (Repeat Performance, USA 1947 and Twilight Zone: Judgement Day, USA 1959) will raise the question how singular the recent wave of loop films are from a historical perspective.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.007
Scholarly communication0.0060.006
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0100.001

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.

Opus teacher head0.027
GPT teacher head0.245
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2021
Admission routes1
Has abstractyes

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