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Record W2176760985 · doi:10.18192/analyses.v10i3.1405

Le joueur bavard. Vers une typologie du dialogue dans le jeu vidéo

2015· article· fr· W2176760985 on OpenAlexaffvenue
Jérôme-Olivier Allard

Bibliographic record

VenueAnalyses Revue de littératures franco-canadiennes et québécoise · 2015
Typearticle
Languagefr
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesPhilosophyArt

Abstract

fetched live from OpenAlex

Cet article, qui s’inscrit dans une réflexion plus large sur les recoupements entre littérature et jeu vidéo, défend la thèse selon laquelle le dialogue dans Dragon Age II, qui occupe plusieurs fonctions héritées d’autres médias ou propres aux œuvres vidéoludiques, participe à la construction de l’univers fictionnel et enrichit l’expérience du joueur. Pour ce faire, la démonstration définit brièvement les notions de jeu et de récit vidéoludique, avant de préciser les formes qu’adopte le dialogue dans Dragon Age II de même que les fonctions qu’il remplit.

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)0.001
metaresearch head score (Gemma)0.003
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: none
Teacher disagreement score0.749
Threshold uncertainty score0.499

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0130.010
Scholarly communication0.0080.004
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0120.001

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 head0.038
GPT teacher head0.293
Teacher spread0.254 · 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

Citations1
Published2015
Admission routes2
Has abstractyes

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