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Record W2809099915 · doi:10.4000/sdj.974

La mise au jeu mise en récit 

2018· article· fr· W2809099915 on OpenAlexaff
­Carl Therrien

Bibliographic record

VenueSciences du jeu · 2018
Typearticle
Languagefr
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesArtPhysicsPhilosophy

Abstract

fetched live from OpenAlex

Cet article présente un système d’analyse qui permet de documenter l’émergence, la prolifération et l’hybridation des différentes configurations ludiques dans l’histoire du jeu vidéo. Ce système prend acte du potentiel et des limitations de différents modèles et méthodes formalistes et de différentes ontologies du jeu. Il repose d’abord sur la segmentation de l’expérience ludique en fonction des figures d’interactivité modélisées dans le système du jeu, puis sur la modélisation de l’action à travers trois couches d’interface et les modalités de performance associées à chacune des figures. Le SHAC (Système Historico-Analytique Comparatif) s’inspire à la fois des acquis de la ludologie et de la narratologie transmédiale, et permet de réaliser des analyses pointues des différentes configurations ludiques de manière uniforme.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.951
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.011
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.003

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 head0.030
GPT teacher head0.308
Teacher spread0.278 · 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; both teacher heads agree on what is shown here.

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".

Quick stats

Citations1
Published2018
Admission routes1
Has abstractyes

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