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Record W2951034822 · doi:10.1177/0093650219852857

Bidirectional Socialization: An Actor-Partner Interdependence Model of Internet Self-Efficacy and digital Media Influence Between Parents and Children

2019· article· en· W2951034822 on OpenAlexaff
Sara Nelissen, Leon Kuczynski, Lennert Coenen, Jan Van den Bulck

Bibliographic record

VenueCommunication Research · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsSocializationPsychologyMedia useThe InternetDigital mediaSocial psychologyDevelopmental psychologyAssociation (psychology)Political science

Abstract

fetched live from OpenAlex

Media researchers have studied how parents and children influence and guide each other’s media use. Although parent and child socialization and influence are thought to be bidirectional, they are usually studied separately, with an emphasis on parental socialization, influence, and guidance of the child’s media use. In this article, we present results from a study that investigates perceived bidirectional digital media socialization between parents and children from the same household ( N = 204 parent-child dyads). This study simultaneously tested parent-to-child and child-to-parent influence using the actor-partner interdependence model to examine the association between perceived Internet self-efficacy and perceived digital media influence. Although the results showed significant cross-sectional actor and partner effects for Internet self-efficacy and perceived digital media influence, these effects largely disappeared in a longitudinal setting.

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)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.098
GPT teacher head0.405
Teacher spread0.307 · 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 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

Citations21
Published2019
Admission routes1
Has abstractyes

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