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Record W4320519469 · doi:10.1145/3569009.3572744

Making From Home: Reflections on Crafting Tangible Interfaces for Stay-at-home Living

2023· article· en· W4320519469 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsQueen's University
FundersMitacsQueen's University
KeywordsHome automationComputer scienceHuman–computer interactionAssisted livingInternet privacyTelecommunicationsGerontologyMedicine

Abstract

fetched live from OpenAlex

Pandemic lockdowns created new barriers for HCI researchers, but also provided new opportunities for deeper engagement and reflection in our home environments. Five participants were introduced with a design brief on self-isolation and engaged 12 of their friends and family in the design process of in-the-isolated-wild deployments. By analysing the design process, we found that –while ‘making from home’– our participants noticed the subtlety of the interactions and materials, the processes of remembrance embedded in craft, the use of imperfection and metaphor in homeware, and how ambient presence can provide emotional support. We then conducted a follow-up study on the benefits and limitations of using a crafting approach while ‘making from home’ and discuss the tensions that novices experience while designing TUIs in such an environment. Our results expand the literature by highlighting the benefits, limitations, and trade-offs of user-led design, DIY user empowerment, and harnessing the power of craft.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.331
Threshold uncertainty score0.683

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.133
GPT teacher head0.395
Teacher spread0.261 · 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

Quick stats

Citations14
Published2023
Admission routes2
Has abstractyes

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