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Record W4200537343 · doi:10.32920/ifmj.v1i2.1498

Old Plays, New Narratives

2021· article· en· W4200537343 on OpenAlexvenueno aff
Daisy Abbott

Bibliographic record

VenueInteractive Film and Media Journal · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsnot available
Fundersnot available
KeywordsNarrativeMovie theaterFandomContext (archaeology)Interpretation (philosophy)Visual artsCitizen journalismParticipatory cultureSociologySocial mediaMedia studiesAestheticsArtMultimediaComputer scienceHistoryLiteratureWorld Wide Web

Abstract

fetched live from OpenAlex

When a theatrical performance is digitally broadcast live to cinemas, the limitations of temporal and spatial specificity are removed and the theatrical experience is simultaneously opened up to a wider audience and inherently altered. One such production, Coriolanus (Donmar Warehouse, 2013-14), starring an actor with a particularly enthusiastic online fan community, was broadcast to cinemas by National Theatre Live, where fans recorded it on digital devices, extracted clips and produced animated gifs, which they captioned to reinterpret the play, sharing them online, removed from their original context. The transformation of theatre texts to cinemas to social media platforms raises exciting questions related to how fans interact with culture both as consumers and as producers of new media texts. How do the different transformations (technical and actively fan-produced) affect both the narrative and the cultural experience? How do new texts function as surrogates for, and extensions of, the ‘official' narrative, as well as new interactive narratives in their own right? This paper addresses these questions in the context of a specific theatrical event as it crossed the boundary from a live, co-located experience first into cinema, and then into interactive hypertexts and memes. Drawing on theories of fandom and participatory culture, as well as post-Web 2.0 analyses of Internet behaviours, the paper examines fan production of new media texts and how they both transmit and transform the source narrative via interpretation, re-interpretation, and misinterpretation. Image Credit: Still of fromhiddleswithlove (2014)

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)0.000
metaresearch head score (Gemma)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.833
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.314
Teacher spread0.292 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2021
Admission routes1
Has abstractyes

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