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Record W4377818775 · doi:10.16995/dscn.9621

Diversity of Immersion Mechanics in Videoludic Novels

2023· article· en· W4377818775 on OpenAlexaffvenue
Lescouet Emmanuelle, P Dumoulin

Bibliographic record

VenueDigital Studies / Le champ numérique · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsUniversité du Québec à MontréalUniversité de Montréal
Fundersnot available
KeywordsNarrativeEntertainmentReading (process)Immersion (mathematics)ArtPsychologySociologyHumanitiesVisual artsLiteraturePhilosophyLinguisticsMathematics

Abstract

fetched live from OpenAlex

Interactive fictions are digital narrative artworks that require little to no dexterity. Indeed, these multimedia fictions do not require a particular proficiency in their manipulation to access and explore the story. However, they do demand distinct mechanics and reading moves, specific to narrative models. These items, between literary and videogame studies, call for the analyses of their own modes of interaction and consumption. In this specific environment, reading, as a form of entertainment, is voluntary and engaged. Since there is a tacit contract with the work that the reader agrees to, which establish the expectation horizon and convey reading habits, our study qualifies this reading experience as immersion, plunging into a second world, and exploring the possibilities it offered. In this article, immersion is defined as an entertainment experience where the human subjects get lost inside the text, they are incorporated in it. They find themselves in the narrative and feelsits affects. We must therefore consider a continuum between artworks relying onfew interactions –even minimal and repeated actions– and others that require more complex sequences. Les fictions interactives sont des œuvres d'art narratives numériques qui ne requièrent que peu ou pas de dextérité. En effet, ces fictions multimédias ne requièrent pas de compétences particulières dans leur manipulation pour accéder à l'histoire et l'explorer. Cependant, ils exigent des mécanismes et des mouvements de lecture distincts, propres aux modèles narratifs. Ces éléments, entre études littéraires et études vidéoludiques, appellent à l'analyse de leurs propres modes d'interaction et de consommation. Dans cet environnement spécifique, la lecture, en tant que forme de divertissement, est volontaire et engagée. Puisqu'il existe un contrat tacite avec l'œuvre que le lecteur accepte, qui établit l'horizon d'attente et transmet des habitudes de lecture, notre étude qualifie cette expérience de lecture d'immersion, de plongée dans un second monde, et d'exploration des possibilités qu'il offre. Dans cet article, l'immersion est définie comme une expérience de divertissement où les sujets humains se perdent dans le texte, ils y sont incorporés. Ils se retrouvent dans le récit et en ressentent les effets. Nous devons donc considérer un continuum entre les œuvres d'art reposant sur peu d'interactions - même des actions minimales et répétées - et d'autres qui requièrent des séquences plus complexes.

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)0.005
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: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.004
Scholarly communication0.0050.003
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.050
GPT teacher head0.304
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

Citations2
Published2023
Admission routes2
Has abstractyes

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