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Jean Châteauvert, Gilles Delavaud, dirs, D’un écran à l’autre, les mutations du spectateur

2016· article· fr· W2603137662 on OpenAlexaboutno aff
Laurent Collet

Bibliographic record

VenueQuestions de communication · 2016
Typearticle
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

Notes de lecture notes de lecture Jean châteauvert, Gilles delavaud, dirs, D'un écran à l'autre, les mutations du spectateur Paris, Éd.L'Harmattan, coll.Les Médias en actes, 2016, 604 pages Ce livre coordonné par Jean Châteauvert et Gilles Delavaud fait suite à un colloque international organisé en 2014 par l'Institut national de l'audiovisuel (Ina), l'université Paris 8 et l'université du Québec à Chicoutimi, qui cherchait à répondre à la question suivante : « de la multiplication des écrans, faut-il conclure à une mutation du spectateur ?» (p.13).La réponse tient en 43 textes représentant près de 600 pages.Ces textes sont regroupés en quatre parties.La deuxième partie regroupe des contributions qui interrogent la notion même de spectateur.La seconde traite des nouvelles possibilités expressives transmédiatiques.La troisième partie décrit des usages apparus avec les changements de contexte technologique et de programmation des diffuseurs.La quatrième combine les trois premières approches pour interroger les nouvelles pratiques de consommation.Le tout est clairement exposé dans l'introduction (pp.13-21) qui propose un résumé de chaque contribution dans l'ordre de leur publication.Tout en respectant le découpage en parties, nous ne ferons pas de même en leur sein, afin de mettre en dialogue ce que nous avons pu lire.

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)0.003
metaresearch head score (Gemma)0.013
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: Other · Consensus signal: none
Teacher disagreement score0.064
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0100.006
Scholarly communication0.0110.007
Open science0.0010.002
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0200.006

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 head0.122
GPT teacher head0.296
Teacher spread0.173 · 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
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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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