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Record W1506666487 · doi:10.15353/joci.v8i1.3061

Too Old For Technology? How The Elderly Of Lisbon Use And Perceive ICT

2012· article· en· W1506666487 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Journal of Community Informatics · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsnot available
Fundersnot available
KeywordsInformation and Communications TechnologyMobile phoneThe InternetDigital dividePhonePerceptionInternet privacySample (material)Stratified samplingAdvertisingPsychologyBusinessComputer scienceWorld Wide WebTelecommunicationsMedicine

Abstract

fetched live from OpenAlex

The elderly have traditionally been an excluded group in the deployment of Information and Communication Technologies (ICT). Even though their use of ICT is increasing, there is still a significant age-based digital divide. To empower elderly people’s usage of ICT we need to look at their patterns of usage and perceptions. To understand how Portugal’s elderly (65 and above) use and perceive mobile phones, computers and the Internet, we surveyed a random stratified sample of 500 individuals over 64 years of age, living in Lisbon. Of those surveyed, 72% owned a mobile phone, 13% used computers, and 10% used the Internet. The quantitative data was followed-up by ten qualitative (semi-structured) interviews. The implications of the results are discussed herein. Keywords: Elderly, Aging, ICT, Ageism, Digital Divide, Mobile phones, Computers, Internet, Portugal, “faux users”

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.035
Threshold uncertainty score0.725

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.050
GPT teacher head0.302
Teacher spread0.252 · 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