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Record W3109244238 · doi:10.1177/1555412020973823

Reading Ren’Py: Game Engine Affordances and Design Possibilities

2020· article· en· W3109244238 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueGames and Culture · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsConcordia University
FundersFonds de Recherche du Québec-Société et Culture
KeywordsAffordanceGame engineGame designComputer scienceFocus (optics)Game DeveloperGame mechanicsProduction (economics)Human–computer interaction

Abstract

fetched live from OpenAlex

Game engines have largely become synonymous with the production of certain game genres, and creating games outside those genres is at the least cumbersome if not outright impossible to do. This study demonstrates how the affordances and constraints of particular engines, working in consort with the creative community around a particular engine, shape both game engine use as well as the game engine thinking that determines what is and is not possible. It does so by looking at a game project developed using the Ren’py engine. Using Fiadotau and Bogost as conceptual springboards, we focus on our decision to use Ren’py and how that decision shaped the game and our production processes. In addition to discussing the engine itself, we also look at how the practices and discourse of the Ren’py community—most notably represented on the engine’s official forums—also shaped our work.

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.

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 score0.949
Threshold uncertainty score0.264

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 head0.025
GPT teacher head0.262
Teacher spread0.237 · 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