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Record W2940907653 · doi:10.1145/3290605.3300239

To Asymmetry and Beyond!

2019· article· en· W2940907653 on OpenAlexafffund
John Harris, Mark Hancock

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicVirtual Reality Applications and Impacts
Canadian institutionsUniversity of Waterloo
FundersOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaSamsung
KeywordsSocial connectednessPerceptionPsychologyAction (physics)AsymmetryHuman–computer interactionComputer scienceGame mechanicsSocial psychologyCognitive psychologyPhysics

Abstract

fetched live from OpenAlex

Social play can have numerous health benefits but research has shown that not all multiplayer games are effective at promoting social engagement. Asymmetric cooperative games have shown promise in this regard but the design and dynamics of this unique style of play is not yet well understood. To address this, we present the results of two player experience studies using our custom prototype game Beam Me 'Round, Scotty! 2: the first comparing symmetric cooperative play (e.g., where players have the same interface, goals, mechanics, etc.) to asymmetric cooperative play (e.g., where players have differing roles, abilities, interfaces, etc.) and the second comparing the effect of increasing degrees of interdependence between play partners. Our results not only indicate that asymmetric cooperative games may enhance players' perceptions of connectedness, social engagement, immersion, and comfort with a game's controls, but also demonstrate how to further improve these outcomes via deliberate mechanical design changes, such as changes in cooperative action timing and direction of dependence.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.038
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0020.005
Scholarly communication0.0050.006
Open science0.0010.008
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0380.008

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 head0.010
GPT teacher head0.255
Teacher spread0.245 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations81
Published2019
Admission routes2
Has abstractyes

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Same topicVirtual Reality Applications and ImpactsFrench-language works237,207