MétaCan
Menu
Back to cohort
Record W2033669857 · doi:10.1016/j.intcom.2006.08.008

Video game values: Human–computer interaction and games

2006· article· en· W2033669857 on OpenAlexaff
Pippin Barr, James Noble, Robert Biddle

Bibliographic record

VenueInteracting with Computers · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsCarleton University
Fundersnot available
KeywordsComputer scienceVideo gameHuman–computer interactionVideo game designGame mechanicsMultimediaFocus (optics)Turns, rounds and time-keeping systems in gamesGame testingGame designGame DeveloperVideo game developmentSoftwareEmergent gameplayInterface (matter)Game design document

Abstract

fetched live from OpenAlex

Current human–computer interaction (HCI) research into video games rarely considers how they are different from other forms of software. This leads to research that, while useful concerning standard issues of interface design, does not address the nature of video games as games specifically. Unlike most software, video games are not made to support external, user-defined tasks, but instead define their own activities for players to engage in. We argue that video games contain systems of values which players perceive and adopt, and which shape the play of the game. A focus on video game values promotes a holistic view of video games as software, media, and as games specifically, which leads to a genuine video game HCI.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.009
Scholarly communication0.0080.006
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.013
GPT teacher head0.289
Teacher spread0.276 · 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 designTheoretical or conceptual
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

Citations226
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueInteracting with ComputersSame topicDigital Games and MediaFrench-language works237,207