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Record W2329070734 · doi:10.1386/jafp.7.2.155_7

Introduction: Film adaptation in the post-cinematic era

2014· article· en· W2329070734 on OpenAlexaff
Russell Kilbourn, Patrick Faubert

Bibliographic record

VenueJournal of Adaptation in Film & Performance · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicShakespeare, Adaptation, and Literary Criticism
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsAdaptation (eye)MediationDialogicPresuppositionMovie theaterSociologyIdentity (music)Field (mathematics)Emphasis (telecommunications)AestheticsNew mediaMedia studiesHistoryPolitical scienceArtSocial scienceEpistemologyPsychologyLawArt history

Abstract

fetched live from OpenAlex

Abstract In recent years, adaptation studies has emerged as a field of urgent scholarly importance and, having moved past outdated presuppositions and prejudices, has revealed adaptation as a crucial form of dialogue between and among different media, texts and social–historical contexts. The proliferation of new technologies and new media, theorized as the digital post-cinematic era, but encompassing more than what Costas Constandinides calls the ‘post-­celluloid’ (2010: 3), has arguably deepened this importance, implicating adaptation in previously unconsidered cultural arenas. In their common emphasis upon post-millennial cinema, all four articles in this dossier are based in the recognition that it is no longer possible to conceive of filmic adaptation as a straightforward movement from page to screen; that therefore we must turn our attention to the role new media technologies play in processes of dialogic mediation and identity formation, in the production (and elision) of inter-subjective and cultural difference, in the shaping of cultural memory, and in the very question of defining cinema in the early twenty-first century.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.580
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.220
Teacher spread0.197 · 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 teacher head, not a consensus.

Study designQualitative
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

Citations1
Published2014
Admission routes1
Has abstractyes

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