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Record W2104693797 · doi:10.1145/2556288.2557198

Exploring video streaming in public settings

2014· article· en· W2104693797 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
TopicInnovative Human-Technology Interaction
Canadian institutionsUniversity of CalgarySimon Fraser University
Fundersnot available
KeywordsDistractionComputer scienceLive streamingMultimediaInternet privacyVideo streamingWearable computerSpace (punctuation)Human–computer interactionShared spacePsychologyComputer network

Abstract

fetched live from OpenAlex

Our research explores the use of mobile video chat in public spaces by people participating in parallel experiences, where both a local and remote person are doing the same activity together at the same time. We prototyped a wearable video chat experience and had pairs of friends and family members participate in 'shared geocaching' over distance. Our results show that video streaming works best for navigation tasks but is more challenging to use for fine-grained searching tasks. Video streaming also creates a very intimate experience with a remote partner, but this can lead to distraction from the 'real world' and even safety concerns. Overall, privacy concerns with streaming from a public space were not typically an issue; however, people tended to rely on assumptions of what were acceptable. The implications are that designers should consider appropriate feedback, user disembodiment, and asymmetry when designing for parallel experiences.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.770
Threshold uncertainty score0.313

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.094
GPT teacher head0.269
Teacher spread0.175 · 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

Citations73
Published2014
Admission routes1
Has abstractyes

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