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Record W2800410905 · doi:10.7202/1086811ar

Involving Older and Disabled People in Assessment of Product,Environment and Service Designs

2011· article· en· W2800410905 on OpenAlexvenueno aff
Ruth Sims, Russell Marshall, S Summerskill, Keith Case, Diane Gyi, Paul Davis

Bibliographic record

VenueDéveloppement Humain Handicap et Changement Social · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsnot available
Fundersnot available
KeywordsDisabled peopleOlder peopleEmpathyProduct (mathematics)Service (business)Design for AllProduct designWork (physics)Universal designPsychologyApplied psychologyComputer scienceHuman–computer interactionEngineeringGerontologyMedicineWorld Wide WebSocial psychologyBusinessMarketing

Abstract

fetched live from OpenAlex

For over 10 years research has been conducted by the Design School at Loughborough University in the United Kingdom (UK) into accessibility of products, services and environments with a particular focus on the needs of older and disabled people. As part of this research a computer based tool called HADRIAN has been developed to encourage empathy between designers, planners and people who are older or who may have some form of impairment. In addition, the tool provides a means to evaluate the accessibility and inclusiveness of a design by simulating the abilities of older and disabled people and performing virtual user trials where potential barriers introduced by the proposed design can be identified and rectified before the design is implemented in the real world. The paper will present and discuss the need for this work and tool, and the importance of obtaining data directly from older and disabled people, as well as three validation trials conducted to evaluate the simulation capabilities of HADRIAN compared to real people interacting with the same tasks.

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)0.013
metaresearch head score (Gemma)0.035
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 score0.013
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.035
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.084
GPT teacher head0.335
Teacher spread0.251 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

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