MétaCan
Menu
Back to cohort
Record W2904586740 · doi:10.1145/3243213

From Being There to Watching

2018· article· en· W2904586740 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 · 2018
Typearticle
Languageen
FieldPsychology
TopicSocial Robot Interaction and HRI
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAttendanceRobotComputer scienceTeleroboticsHuman–computer interactionComputer-supported cooperative workPresentation (obstetrics)VideoconferencingTheme (computing)TeleoperationMultimediaWork (physics)World Wide WebMobile robotEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Telepresence attendance at academic conferences is now a reality and allows people who cannot attend in person with the opportunity to still be “present.” This is valuable for people who face accessibility challenges, cost or travel restrictions, or limited time for travel. We have deployed and studied the use of telepresence robots at three ACM conferences, Ubicomp/ISWC 2014, CSCW 2016, and CHI 2016, ranging from remote users having dedicated telepresence robots to users sharing telepresence robots both synchronously and asynchronously. In this article, we report on the telepresence offerings along with the user behaviors, experiences, and the social norms found for remote conference attendance. Our results across the studies focus around three main themes: shared vs. dedicated robot usage, identity presentation and the value and challenges associated with it; and local in-person support through proxies and instant messaging backchannels. These themes point to three different areas of design exploration for telepresence robots, pointing out the limitations of existing design solutions with respect to each theme, areas for future telepresence design work, and the value in considering varied telepresence robot solutions, including both dedicated and shared telepresence robots.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.893
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0170.007

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 head0.051
GPT teacher head0.397
Teacher spread0.346 · 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