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Record W2058073470 · doi:10.1145/1936652.1936676

Proxemic interaction

2010· article· en· W2058073470 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInteractive and Immersive Displays
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsProxemicsHuman–computer interactionComputer scienceExploitIdentity (music)Orientation (vector space)Identification (biology)CommunicationPsychologyAestheticsMathematicsComputer security

Abstract

fetched live from OpenAlex

In the everyday world, much of what we do is dictated by how we interpret spatial relationships, or proxemics. What is surprising is how little proxemics are used to mediate people's interactions with surrounding digital devices. We imagine proxemic interaction as devices with fine-grained knowledge of nearby people and other devices -- their position, identity, movement, and orientation -- and how such knowledge can be exploited to design interaction techniques. In particular, we show how proxemics can: regulate implicit and explicit interaction; trigger such interactions by continuous movement or by movement of people and devices in and out of discrete proxemic regions; mediate simultaneous interaction of multiple people; and interpret and exploit people's directed attention to other people and objects. We illustrate these concepts through an interactive media player running on a vertical surface that reacts to the approach, identity, movement and orientation of people and their personal devices.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.766
Threshold uncertainty score0.990

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 head0.007
GPT teacher head0.261
Teacher spread0.254 · 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

Quick stats

Citations401
Published2010
Admission routes1
Has abstractyes

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