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Record W1479934904 · doi:10.15353/joci.v8i1.3052

Revisited: Communication Media Use in the Grandparent/Grandchild Relationship

2012· article· en· W1479934904 on OpenAlexvenueno aff
Ulla Bunz

Bibliographic record

VenueThe Journal of Community Informatics · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsnot available
Fundersnot available
KeywordsGrandparentPhoneInstant messagingPsychologyLandlineDemographicsQuality (philosophy)Mobile phoneQuality timeGrandchildFace (sociological concept)Social psychologyDevelopmental psychologyComputer scienceFocus groupDemographyWorld Wide WebSociology

Abstract

fetched live from OpenAlex

This study extends and replicates some of Harwood’s (2000) earlier research investigating media use in interactions between grandparents and grandchildren. More specifically, this research extends Harwood’s work by adding the technologies of the cell phone, email, and instant messenger to the media he investigated (face-to-face, written documents, and telephone). Such a study allows finding out whether the availability of new technologies has any effect on the grandparent/grandchild relationship. Sixty-six dyads (N = 132) of grandchildren and grandparents participated in the study, completing a questionnaire on basic demographics, media use, and relational quality. Results show usage divides between grandchildren and grandparents, as well as within the grandparent group. The cell phone and face-to-face interaction are used most frequently in the grandparent/grandchild relationship. Technologies such as email or instant messenger are not used much even across the geographic distance they were designed to overcome. Follow up tests to a significant ANOVA did not show significant results for medium type chosen based on who initiates contact. Face-to-face remains the strongest predictor of quality inter-generational relationships, followed by use of the cell phone, the landline phone, and email (in that order). Findings are discussed in light of both media richness theory and the social influence model.

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)0.010
metaresearch head score (Gemma)0.003
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 score0.354
Threshold uncertainty score0.747

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.105
GPT teacher head0.330
Teacher spread0.225 · 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 designQualitative
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

Citations10
Published2012
Admission routes1
Has abstractyes

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