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Record W2901641489 · doi:10.14236/ewic/hci2018.142

Designing Human-Robot Interaction for Dependent Elderlies: a Living Lab Approach

2018· article· en· W2901641489 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

VenueElectronic workshops in computing · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovative Approaches in Technology and Social Development
Canadian institutionsBerger (Canada)
Fundersnot available
KeywordsParticipatory designRobotHuman–computer interactionHuman–robot interactionLiving labProcess (computing)Assisted livingComputer scienceInteraction designReflection (computer programming)Citizen journalismMobile robotSocial robotIndependent livingSocial relationUser-centered designArtificial intelligencePsychologyEngineeringRobot controlSocial psychologyWorld Wide Web

Abstract

fetched live from OpenAlex

This paper describes the design and evaluation process of a mobile social robotic solution for elderlies, following a living lab approach. The living lab approach combines the principles of human-centred approach and participatory design. The research question at the heart of this study is whether a proper understanding of needs and participation of stakeholders in the design process ensures usefulness and acceptance of the solution. Informed by fieldwork in a retirement home, a prototype of human-robot interaction has been iteratively designed and evaluated with the participation of users. This HRI design serves as the basis to examine the practical acceptance this social robot interaction, as a first step to a broader reflection about the social acceptability of social robots. The first insights of this study are presented in this paper.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.747
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.031
GPT teacher head0.285
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