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Record W2529208981

Root of Play - Game Design for Digital Humanists

2015· article· en· W2529208981 on OpenAlexaffabout
Andy Keenan, Matt Bouchard

Bibliographic record

VenueSyllabus · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGame art designRoot (linguistics)Game designVideo game designGame design documentVideo game developmentGame DeveloperComputer scienceCreativityMultimediaSimple (philosophy)Stylized factGame mechanicsBrainstormingMathematics educationPsychologyArtificial intelligenceSocial psychology
DOInot available

Abstract

fetched live from OpenAlex

Root of Play (stylized as √play) is a simple card game used to generate game design ideas in a short period of time. This game was designed to meet the needs of a unique classroom – a weeklong intensive summer workshop with students ranging from undergraduates to full professors. The purpose of Root of Play is combining theoretical discussions of games with practical applications of game design. The result is a card game that generates playable games. Using the principle of creativity through constraint, Root of Play leads students from brainstorming to playable prototypes. The game is suitable for all levels of gamers, from novices to game designers. Cards provide prompts and frameworks for players to make simple games and test out different development ideas. Currently, the game is utilized at the Digital Humanities Summer Institute in Victoria, BC, Canada.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.897
Threshold uncertainty score0.211

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.075
GPT teacher head0.325
Teacher spread0.250 · 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 designNot applicable
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
Published2015
Admission routes2
Has abstractyes

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