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Record W6954982401 · doi:10.57698/v17i1.04

deformTable: A design inquiry and long-term field study into creative and contingent appropriations of a shape-changing artifact

2023· article· en· W6954982401 on OpenAlexaff

Bibliographic record

VenueTU/e Research Portal · 2023
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsSimon Fraser UniversityUniversity of Waterloo
Fundersnot available
KeywordsArtifact (error)Materiality (auditing)Field (mathematics)Empirical researchEveryday lifeEmpirical evidence

Abstract

fetched live from OpenAlex

In this paper, we propose that a materiality approach can sustain creative and contingent appropriations of a particular shape-changing artifact in everyday settings over time. We support this proposal by designing and deploying five deformTables to five households for approximately one year to gather empirical insights. deformTable is a shape-changing artifact that can go up with the change in weight or pressure applied to its top surface. Findings suggest that participants adopted the shape-changing artifact for routine exercises and ludic purposes in the early months of living with deformTable. Some further decorated the shape-changing interface with tools in their homes, while others sketched and performed music with deformTable. Over time, deformTable provoked rich experiences of creative actions across different homes. Reflecting on these empirical findings contributes implications for further explorations on designing for ludic appropriation, individual improvisation, and shape-changing interfaces to be shaped through use.

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)0.011
metaresearch head score (Gemma)0.015
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 score0.011
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0040.008
Scholarly communication0.0040.004
Open science0.0020.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.103
GPT teacher head0.404
Teacher spread0.301 · 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
Published2023
Admission routes1
Has abstractyes

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