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Record W2314992637 · doi:10.1386/josc.2.2.229_1

Greenaway’s books: Peter Greenaway’s published screenplays

2011· article· en· W2314992637 on OpenAlexaff
Miguel Mota

Bibliographic record

VenueJournal of Screenwriting · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicArtistic and Creative Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsScripting languageNarrativeArtLiteratureReading (process)Visual artsArt historyComputer sciencePhilosophyLinguistics

Abstract

fetched live from OpenAlex

Greenaway’s published screenplays – screenplays produced and consumed as discrete material objects – function both as fluid, hybrid texts and as material books that stand ambivalently and therefore suggestively and productively poised between print and film technologies. Ranging from the early scripts published by Faber and Faber in the mid-to-late 1980s to the later and still-ongoing series of scripts produced by the French publisher Dis Voir, Greenaway’s published screenplays are fascinating examples of print film texts that produce and demand unique ways of reading and looking. By addressing these books as visual and material objects, distinct from the films, we might evince and extract from the pages of these published screenplays entirely new texts with a plurality of narrative possibilities, in which juxtapositions and relationships amongst different cultural discourses can give rise to innovative visual and verbal structures. Such an approach to Greenaway’s published film scripts as material events might contribute a curious but compelling chapter to the history of the ontology of the screenplay, affording the published script a visibility it often otherwise lacks.

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)0.000
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: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.059
Threshold uncertainty score0.197

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0040.003
Scholarly communication0.0070.006
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0590.010

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 head0.118
GPT teacher head0.269
Teacher spread0.151 · 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
GenreReview

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
Published2011
Admission routes1
Has abstractyes

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