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Record W4311479744 · doi:10.4000/resf.11364

Gestes de lecture numérique et lecture immersive de science-fiction

2022· article· fr· W4311479744 on OpenAlexaff
Lescouet Emmanuelle

Bibliographic record

VenueReS Futurae · 2022
Typearticle
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

La science-fiction investit la littérature numérique, tant par ses thématiques que par l’envie même de rêver des formes littéraires du futur, permettant de convoquer les technologies pour écrire des mondes de SF au plus près des besoins des œuvres. La littérature numérique, quant à elle, offre à la science-fiction un éventail de formes et de gestes de lecture nous permettant de repenser l’immersion (cf. Ryan, Triclot). Il est nécessaire de comprendre comment ces derniers permettent une superposition du monde second et du quotidien du.de la lecteur.rice pour envisager les narrations numériques de science-fiction. Ainsi, les notifictions (Bouchardon, 2012), comme la série Lifeline, en incluant la durée extradiégétique, l’attente et des interfaces intimes de messagerie, superposent les temporalités, tandis que des œuvres géolocalisées, comme It Must Have Been Dark by Then, permettent d’apercevoir les lieux qui nous entourent, comme décors futuristes ou dystopiques. La présence même d’un moyen d’interaction entre les mains du.de la lecteur.ice le.a place dans une position particulière de réception et d’exploration de l’univers. Ce dernier influera également, rapprochant l’œuvre du corps lorsqu’elle convoque du tactile ou sur casque VR, mais à l’inverse le mettant à distance avec une manette.

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 categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.703
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
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.082
GPT teacher head0.306
Teacher spread0.224 · 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
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

Citations3
Published2022
Admission routes1
Has abstractyes

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