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Record W4389815623 · doi:10.4000/sdj.5946

Pour une harmonie de raison et de perception

2023· article· fr· W4389815623 on OpenAlexaff
Clément Personnic

Bibliographic record

VenueSciences du jeu · 2023
Typearticle
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPhilosophyHumanitiesPsychology

Abstract

fetched live from OpenAlex

La dissonance ludo-narrative est un concept important dans le domaine des études (vidéo)ludiques. À la fois cristallisation de débats épistémologiques anciens et outil pratique pour parler d’expérience ou de structure, cette notion demeure en fait assez floue, perdue entre les différentes désignations auxquelles renvoie la « ludo-narrativité ». L’acception rapide de la notion est la conséquence d’une super-applicabilité, au sens d’une utilité pratique et instinctive dans de nombreuses disciplines, qu’il faut remettre en question en raison d’une présentation initiale mal circonscrite. Par l’entremise d’une approche historiographique et théorique, cet article propose de mettre en lumière cette insuffisance et la façon dont elle met en jeu un problème de raison et de perception à remédier. Nous montrerons également comment cette insuffisance de plus en plus perceptible génère des réponses de la part des chercheurs par des travaux offrant – malgré certaines limites – de nouvelles avenues de réflexions dont le recours à la théorie de l’harmonie tonale.

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)0.006
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0050.057
Scholarly communication0.0150.022
Open science0.0020.008
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0110.001

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 head0.357
GPT teacher head0.386
Teacher spread0.029 · 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 designTheoretical or conceptual
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

Citations0
Published2023
Admission routes1
Has abstractyes

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