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Record W2028926124 · doi:10.1145/1296843.1296871

Using participatory activities with seniors to critique, build, and evaluate mobile phones

2007· article· en· W2028926124 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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMobile phoneParticipatory designCitizen journalismSoftware deploymentPhoneComputer scienceMobile deviceParticipatory sensingMultimediaMobile computingInternet privacyVariety (cybernetics)Mobile technologyHuman–computer interactionWorld Wide WebEngineeringTelecommunicationsData scienceSoftware engineering

Abstract

fetched live from OpenAlex

Mobile phones can provide a number of benefits to older people. However, most mobile phone designs and form factors are targeted at younger people and middle-aged adults. To inform the design of mobile phones for seniors, we ran several participatory activities where seniors critiqued current mobile phones, chose important applications, and built their own imagined mobile phone system. We prototyped this system on a real mobile phone and evaluated the seniors' performance through user tests and a real-world deployment. We found that our participants wanted more than simple phone functions, and instead wanted a variety of application areas. While they were able to learn to use the software with little difficulty, hardware design made completing some tasks frustrating or difficult. Based on our experience with our participants, we offer considerations for the community about how to design mobile devices for seniors and how to engage them in participatory activities.

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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.359
Threshold uncertainty score0.889

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.044
GPT teacher head0.388
Teacher spread0.344 · 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

Citations127
Published2007
Admission routes1
Has abstractyes

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