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Record W3007972578 · doi:10.7202/1067491ar

I Love Dick et Transparent : de quelques catégories de montage dans la sérialité télévisuelle

2020· article· fr· W3007972578 on OpenAlexaffvenue
Marta Boni, Larissa Estevam Christoforo

Bibliographic record

VenueCinémas Revue d études cinématographiques · 2020
Typearticle
Languagefr
FieldArts and Humanities
TopicArtistic and Creative Research
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

L’article examine les différentes typologies de montage dans deux séries pensées pour les nouveaux services télévisuels de diffusion en continu : Transparent (Jill Soloway, 2014-2019) et I Love Dick (Sarah Gubbins et Jill Soloway, 2016-2017). La posture queer permet de concentrer la multiplicité des options dans un parcours sériel (dans une logique où l’identité se trouve entre plusieurs options). Le montage est entendu comme : a) la relation entre les éléments au sein de l’épisode, semblable au montage cinématographique ; b) la relation des épisodes à la totalité de la saison et de la série ; c) une performance capable de réactiver certaines significations au fil des saisons, par des lectures et réécritures à rebours, qui bouleversent a posteriori le sens de l’ensemble. Si cette dernière catégorie joue avec une traduction un peu abusive du terme editing, elle a le mérite de souligner le geste de « réactivation sérielle » qui permet de mettre en évidence, par les effets de rythme et de mémoire spectatorielle, l’importance du potentiel queer de la sérialité.

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)0.002
metaresearch head score (Gemma)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.018
Scholarly communication0.0110.012
Open science0.0010.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.066
GPT teacher head0.308
Teacher spread0.242 · 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

Citations2
Published2020
Admission routes2
Has abstractyes

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