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Record W2786263873 · doi:10.1177/0008417418754395

Meanings and experiences associated with computer use of older immigrant adults of lower socioeconomic status

2018· article· en· W2786263873 on OpenAlexvenueaboutno aff
Lynne Andonian

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsnot available
Fundersnot available
KeywordsSocioeconomic statusImmigrationGerontologyPsychologyMedicineSociologyDemographyGeography

Abstract

fetched live from OpenAlex

BACKGROUND: Immigrant older adults are a substantial demographic composing 12% to 30% of older adults in the United States and Canada, yet no research has addressed the meanings associated with computer use for low-socioeconomic-status and immigrant older adults. PURPOSE: The study explored the meanings, occupational engagement, and experiences associated with computer use. METHOD: A mixed-methods approach, qualitative participatory action research (photovoice) and survey (Computer Proficiency Questionnaire), was used. Data collection consisted of narratives, focus groups, and Likert scale responses for nine participants. FINDINGS: The participants expressed the meanings they associated with computer use as freedom, personal growth, and engagement. Computers promote occupational engagement in social participation, education, and leisure. IMPLICATIONS: The findings of personal growth may inform occupational therapy interventions using computers to enable adjustment to changes related to aging and wellness. Social participation and education were motivators for computer use, which may inform computer engagement strategies for this population.

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 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.251
Threshold uncertainty score0.989

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 studies0.0000.001
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 head0.042
GPT teacher head0.303
Teacher spread0.261 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations13
Published2018
Admission routes2
Has abstractyes

Explore more

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