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Record W2044944647 · doi:10.1145/2661334.2661375

Technology to reduce social isolation and loneliness

2014· article· en· W2044944647 on OpenAlexafffund
Ron Beacker, Kate Sellen, Sarah Crosskey, Véronique Boscart, Bárbara Barbosa Neves

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsConestoga CollegeOntario College of Art and DesignUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLonelinessSocial isolationIsolation (microbiology)Software deploymentVulnerability (computing)PsychologySocial supportStressorGerontologyInternet privacyComputer scienceSocial psychologyMedicineComputer securityClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

Large numbers of individuals, many of them senior citizens, live in social isolation. This typically leads to loneliness, depression, and vulnerability, and subsequently to other negative health consequences. We report on research focused on understanding the communication needs of people in environments associated with social isolation and loneliness, and how technology facilitates social connection. Our work consists of successive iterations of field studies and technology prototype design, deployment, and analysis. Particular attention is paid to seniors in retirement communities and in long-term care settings (nursing homes). We present design implications for technology to enable seniors' social connections, the "InTouch" prototype that satisfies most of the implications, and a report on one older adult's experience of InTouch.

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)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0000.002
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.015
GPT teacher head0.319
Teacher spread0.305 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations127
Published2014
Admission routes2
Has abstractyes

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