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Record W3043986991 · doi:10.1177/0091415020940200

Innovation in Later Life: A Study of Grandmothers and Facebook

2020· article· en· W3043986991 on OpenAlexfundaboutno aff
Mor Yachin, Galit Nimrod

Bibliographic record

VenueThe International Journal of Aging and Human Development · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicIntergenerational Family Dynamics and Caregiving
Canadian institutionsnot available
FundersConcordia University
KeywordsPsychologyInternet privacyCyberpsychologySocial mediaComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Relying on the Innovation theory of successful aging, this study aims at exploring how grandmothers around the world perceive and use Facebook. Twenty-seven focus groups were set up in seven countries: Canada, Colombia, Israel, Italy, Peru, Romania, and Spain. Participants consisted of 184 grandmothers aged 65 and over who use information and communication technology to some extent. Data were analyzed according to hybrid thematic analysis principles and findings pointed to substantial ambivalence regarding Facebook. Grandmothers who used it reported rather restrained use that was typically triggered externally and characterized by reactive use patterns. Nevertheless, Facebook appeared to promote users' well-being by supporting preservation of their relationships, roots, and sense of relevance. These findings suggest a new theoretical tenet to innovation theory according to which even "restrained innovation" in later life may be beneficial.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.549
Threshold uncertainty score0.106

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 studies0.0000.000
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 head0.031
GPT teacher head0.303
Teacher spread0.272 · 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

Citations12
Published2020
Admission routes2
Has abstractyes

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