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Record W2970653168 · doi:10.15353/kinema.vi.1233

Filmic Space and Real Time in Hitchcock’s Rope

2011· article· en· W2970653168 on OpenAlexvenueno aff
Peter J. Dellolio

Bibliographic record

VenueKinema A Journal for Film and Audiovisual Media · 2011
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCinema and Media Studies
Canadian institutionsnot available
Fundersnot available
KeywordsRopeNarrativeSpace (punctuation)Focus (optics)AestheticsAbstractionArtComputer sciencePhilosophyEpistemologyLiteraturePhysics

Abstract

fetched live from OpenAlex

FILMIC SPACE AND REAL TIME IN HITCHCOCK'S ROPE "Brandon, how did you feel?""When?""During it?"Philip Morgan to Brandon Shaw IntroductionRope explores some of the fundamental characteristics of the cinematic abstraction of time and space by using the mobile camera as an agent that gives plastic reality to subjective material. In Rope, a synthesis of real time and filmic space forces the viewer to absorb narrative information on multiple, often distastefully ironic levels. At the same time, the viewer is given freedom of selection in terms of how, when, and why his/her attention is split, inviting some comparison with similar choices experienced during depth of focus shots, a spatial configuration that Hitchcock characteristically avoided. The movement of the camera throughout the film places the viewer in the ethically, emotionally, and psychologically uncomfortable position of perceiving perversity in the relationship between image and dialogue. For example, during the...

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)0.001
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.021
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.007
Scholarly communication0.0060.004
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.045
GPT teacher head0.245
Teacher spread0.200 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

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