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Record W2465297518 · doi:10.1145/2893182

Accessible Play in Everyday Spaces

2016· article· en· W2465297518 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

VenueACM Transactions on Computer-Human Interaction · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsToronto Metropolitan UniversityCentennial CollegeBrock UniversityUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEntertainmentMixed realityEveryday lifeVirtual realityComputer scienceVariety (cybernetics)MultimediaHuman–computer interactionSpace (punctuation)Exploratory researchField (mathematics)Set (abstract data type)SociologyVisual artsPolitical scienceArtArtificial intelligence

Abstract

fetched live from OpenAlex

The advent of affordable and powerful mobile technology has allowed for explorations in mixed reality that merges virtual and physical space. However, the social and entertainment value and efficacy of mixed reality platforms for adult powered chair users has not been widely explored. In this article, we introduce the Mobility Games project, which aims to produce a series of inclusive entertainment technologies and services for people who use powered chairs. We describe our first offering: an accessible, social mixed reality game for co-located mobile play in everyday spaces. Findings from two exploratory field studies and a post hoc observer survey show that adult powered chair users found the game to be entertaining and used a variety of path strategies as they learned to play the game. An initial set of theoretically and empirically informed guidelines for making mobile mixed reality games accessible to adult powered chair users with diverse abilities is proposed.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.962
Threshold uncertainty score0.963

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.338
Teacher spread0.306 · 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