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Record W2980666138 · doi:10.1080/17458927.2019.1619976

Puzzling pieces: a sensory design learning tool

2019· article· en· W2980666138 on OpenAlex
Eileen Harris, Lois Frankel, Claudie St. Arnaud, Alanna Bamber

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

VenueThe Senses and Society · 2019
Typearticle
Languageen
FieldEngineering
TopicDesign Education and Practice
Canadian institutionsCarleton University
Fundersnot available
KeywordsSensory systemProcess (computing)ConsciousnessCognitive scienceHuman–computer interactionExploratory researchPsychologyDesign processSemantics (computer science)Computer scienceCognitive psychologyEngineeringSociologyWork in processNeuroscience

Abstract

fetched live from OpenAlex

This article gives an account of an activity that is part of a collection of instructional materials for learning about sensory aspects of design for products, environments, and services. It describes the participants’ experiences and reflections in a workshop at DeSForM, the 10th Conference on Design and Semantics of Form and Movement. The article highlights the participants’ engagement with one of the exploratory activities, Puzzling Pieces, that was in the process of being developed. The unique ways in which the attendees translated theoretical multi-sensory design perspectives into activities for heightening multi-sensory awareness and consciousness of sensory interactions suggest that this activity may be a useful tool for finetuning the sensory design process.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.205
Threshold uncertainty score0.209

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.019
GPT teacher head0.228
Teacher spread0.209 · 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