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Record W2196731773 · doi:10.20380/gi2015.24

Synchronous yoga and meditation over distance using video chat

2015· article· en· W2196731773 on OpenAlexaff
Reese Muntean, Carman Neustaedter, Kate Hennessy

Bibliographic record

VenueCanada Human-Computer Communications Society · 2015
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMeditationMultimediaPsychologyComputer scienceApplied psychology

Abstract

fetched live from OpenAlex

Community and social relationships are an important part of yoga and meditation despite the fact that they are commonly perceived as solitary activities. Family members and loved ones often share activities and experiences over video chat technology to sustain their relationships across distance, and we wondered if similar technology could allow for yoga and meditation partners to share their practice remotely. In our study, sixteen participants completed yoga and meditation sessions over distance and participated in semi-structured interviews about their experience. Our results show that video chat can support synchronous yoga and meditation over distance through seeing and hearing one's remote partner. Both video and audio play an important role in creating a sense of remote presence. Yet there are space issues, camera challenges, and issues with a lack of touch for instructional purposes. Future video chat systems for synchronous yoga should consider ways to improve these issues while balancing the need to keep technology in the background.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.088
GPT teacher head0.385
Teacher spread0.296 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations6
Published2015
Admission routes1
Has abstractyes

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