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Record W1846740668

All Singing, All Talking, All Digital: Media Windows and Archiving Practice in the Motion Picture Studios

2008· article· en· W1846740668 on OpenAlexfundvenueno aff
Randal Luckow, James M. Turner

Bibliographic record

VenueArchivaria · 2008
Typearticle
Languageen
FieldArts and Humanities
TopicArt History and Market Analysis
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaNational Science Foundation
KeywordsStudioMovie theaterFilm industryVisual artsRevenueArtMultimediaHumanitiesBusinessComputer science
DOInot available

Abstract

fetched live from OpenAlex

The InterPARES 2 case study on moving images investigated the digital archiving practices of a commercial movie studio with regard to material from a computer-generated animated feature film. The results showed that the traditional neglect of potentially useful archival materials on the part of the movie studios, is carried over into the digital world. In order to explain why good archival practice has not made economic sense to the industry over the years, we review the development of the motion picture industry in relation to cultural property, and argue that the shortsighted vision of the studios deprives them of future profitable options. We look at trends in media packaging and consumption, and speculate that untapped revenue streams currently available and unknown future possibilities provide enough economic incentive for the studios to archive their assets in a systematically or ganized repository. We conclude that the studios stand only to gain from implementing good archiving practice at the time of production, that the victorious players in the fast-moving and unpredictable world of media evolution will be the ones who have the help of professional archivists, and that in the process, cultural heritage materials will get better care than they have ever had before. RÉSUMÉL’étude de cas d’InterPARES 2 sur les images en mouvement a porté sur les pratiques d’archivage numérique d’un studio commercial de cinéma relativement au matériel généré par un film produit par infographie. Les résultats ont montré que le désintérêt traditionnel des studios de production pour les documents qui pourraient avoir une valeur archivistique potentielle s’est transposé dans le monde du numérique. Afin d’expliquer les raisons pour lesquelles l’industrie du cinéma n’arrive pas à croire que les bonnes pratiques archivistiques sont justifiées sur le plan économique, les auteurs examinent le développement de l’industrie cinématographique en lien avec la propriété culturelle et af firment que la vision à court terme des studios les prive de futures occasions de profit. Les auteurs explorent les modes pour ce qui est de l’emballage et de la consommation des médias et ils avancent que les sources de revenus présentement disponibles et non exploitées par les studios, de pair avec les possibilités futures encore inconnues, of frent un incitatif économique suf fisant pour que les studios veillent à l’archivage systématique de leurs documents dans un centre d’archives. Les auteurs concluent que les studios ont tout à gagner en adoptant de meilleures pratiques archivistiques à l’étape de la production cinématographique, que ceux qui travaillent en collaboration avec des archivistes professionnels seront des acteurs gagnants dans le monde rapide et imprévisible de l’évolution des médias et que, dans tout ce processus, les documents du patrimoine culturel auront une considération qu’ils n’ont jamais connue auparavant.

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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0060.006
Scholarly communication0.0090.004
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.026
GPT teacher head0.234
Teacher spread0.207 · 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 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

Citations7
Published2008
Admission routes2
Has abstractyes

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