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Record W4407152991 · doi:10.3233/faia241524

An Irish ‘Traveling’ Air-Purification Robot in a Care Home in Tokyo: Why Do Humanities and Social Science Matter?

2025· book-chapter· en· W4407152991 on OpenAlexaff
Naonori Kodate, Pranav Kohli, Yurie Maeda, Robert Scott, Wenwei Yu, Kazuko Obayashi, Shigeru Masuyama

Bibliographic record

VenueFrontiers in artificial intelligence and applications · 2025
Typebook-chapter
Languageen
FieldEarth and Planetary Sciences
TopicArchaeological Research and Protection
Canadian institutionsCanada Mortgage and Housing Corporation
Fundersnot available
KeywordsIrishHumanitiesSociologyMedia studiesArtPhilosophyLinguistics

Abstract

fetched live from OpenAlex

This paper examines the adoption process of an Irish air-purification robot in a nursing home in Japan. For the three-year project, researchers and engineers, interested in exploring human-robot interactions, formed a transdisciplinary team. Stemming from the concept of user-centered design, one original air-purification robot was produced and tested in one care facility each in Ireland and Japan. The robot ‘traveled’ from Dublin to Tokyo, and spent three months working in a residential care home where its interactions with users were observed. Based on ‘digital technography’ and ‘matters of concern’, the paper describes the research processes, treating this as a journey of the robot, and how it was imagined (at the design stage in Ireland) and reimagined in a different cultural context (at the point of use in Japan). The paper refers to challenges that we as transdilsciplinary researchers encountered along the way, while emphasizing the significance of deciphering the human ‘context’ in which AI and robotics are applied. The paper seeks to answer why humanities and social sciences research matter greatly.

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 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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.967
Threshold uncertainty score0.764

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
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 head0.049
GPT teacher head0.287
Teacher spread0.238 · 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 teacher head, not a consensus.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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