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Record W4399793245 · doi:10.7146/si.v7i3.146570

A Touch of Companionship

2024· article· en· W4399793245 on OpenAlexaboutno aff
An Kosurko, Joseph Webb

Bibliographic record

VenueSocial Interaction Video-Based Studies of Human Sociality · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsInterpersonal relationshipPsychologySocial psychology

Abstract

fetched live from OpenAlex

Dance activities are promoted with a range of benefits in institutional settings for people living with dementia (PLWD) and necessitate the active involvement of companions for engagement. This ethnomethodological study uses multimodal conversation analysis to explore how the role of the companion emerges to engage PLWD in dance activities, with special attention on different uses of touch to support engagement in embodied interactions. Analyses of video recordings focus on interactions between companions and PLWD in both structured and unstructured dance activities in institutional settings in Canada, Finland, and the UK. We demonstrate how companions use touch and other multimodal resources to engage participants with others in dance activities. We argue that the role of the companion emerges in interaction and can shift from participant to participant, including PLWD. We conclude with discussion and recommendations for supporting the engagement of PLWD with sensitivity to how actions obligate responses.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.011
Scholarly communication0.0060.006
Open science0.0010.011
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.292
GPT teacher head0.469
Teacher spread0.177 · 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 designQualitative
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

Citations1
Published2024
Admission routes1
Has abstractyes

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