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Record W2408247118 · doi:10.1145/2851581.2856473

Pervasive Play

2016· article· en· W2408247118 on OpenAlexaff
June Ahn, Elizabeth Bonsignore, Derek L. Hansen, Kari Kraus, Carman Neustaedter

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsSimon Fraser University
FundersNational Science Foundation
KeywordsVariety (cybernetics)Ubiquitous computingVirtual realityComputer scienceEveryday lifeHuman–computer interactionAugmented realityKey (lock)MultimediaMobile deviceWorld Wide WebPolitical science

Abstract

fetched live from OpenAlex

The infusion of mobile and collaborative technologies into our everyday lives enables new forms of pervasive games and play. We use the term pervasive play as shorthand for technology-mediated, playful experiences that are tethered to our everyday lives through the physical and virtual spaces we inhabit. This includes a variety of game and play genres ranging from alternate reality games to urban games to mixed reality performance and playful uses of public displays. The goals of the workshop are to (a) strengthen and broaden the community of pervasive play researchers and practitioners, (b) explore design frameworks for creating novel pervasive play experiences, and (c) identify key research questions, methods, and challenges for future research in this area.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.924
Threshold uncertainty score0.999

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.015
GPT teacher head0.255
Teacher spread0.239 · 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.

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

Citations10
Published2016
Admission routes1
Has abstractyes

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