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Record W2025590540 · doi:10.1080/14626261003654509

Agency as commitment to meaning: communicative competence in games

2010· article· en· W2025590540 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.

Bibliographic record

VenueDigital Creativity · 2010
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsAgency (philosophy)CommitNarrativeCompetence (human resources)Meaning (existential)PleasureEpistemologySociologyComputer sciencePsychologySocial psychologyLinguisticsSocial science

Abstract

fetched live from OpenAlex

Agency has long been considered one of the core pleasures of interacting with digital games. Recent treatments of agency in games culture and game design have grown increasingly concerned with providing the player with limitless freedom to act. While this describes one form of pleasure, in narratively focused games it has the unfortunate consequence of pitting the agency of the player against the will of the designer. We contend that for narrative games it is valuable to refocus our definitions of agency on the notion of meaning, and propose a treatment of agency that emphasises communicative commitments. This form of agency draws on ideas from speech act theory, and relies on a degree of ‘communicative competence’ on the part of both the game designer and player in order to function. We discuss mechanisms for training players in the necessary literacies needed to commit to meanings in games, and provide an example analysis of a game that successfully accomplishes this task.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.561
Threshold uncertainty score0.714

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.023
GPT teacher head0.304
Teacher spread0.281 · 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