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Record W2928642801 · doi:10.7202/1058321ar

Game Design and Affect: How Games Move Us as a Catalyst for Explorations in Game Studies

2019· article· en· W2928642801 on OpenAlexaffvenue
Christopher Hugelmann

Bibliographic record

VenueLoading · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsToronto Metropolitan UniversityYork University
Fundersnot available
KeywordsAffect (linguistics)Game studiesGame designIntersection (aeronautics)Game mechanicsField (mathematics)Game art designObject (grammar)Video game designPsychologySociologySocial psychologyComputer scienceMultimediaMedia studiesEngineeringCommunicationArtificial intelligenceMathematics

Abstract

fetched live from OpenAlex

How Games Move Us: Emotion By Design is an introduction to the ways in which digital games and game studies are slowly encroaching on other territory; in this case, Isbister looks at the intersection of psychology, kinesthetics, design and games and how new notions from these fields alter our understanding of games as a whole. The book is aimed at changing how people talk about and understand digital games, not only as a technical object but as a social medium. Isbister readily accomplishes her goal of highlighting the ways that people can affect and are affected by games, though at times, the book struggles with its strong reliance on examples and dated references to the field of game studies and psychology.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.605
Threshold uncertainty score0.318

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.062
GPT teacher head0.335
Teacher spread0.273 · 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.

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

Citations0
Published2019
Admission routes2
Has abstractyes

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