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The Relationship Between Electronic Device Usage and Relationship Satisfaction

2024· article· en· W4390504686 on OpenAlex
Yiming Pan

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCommunications in Humanities Research · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsInterpersonal communicationPsychologyPerceptionInterpersonal relationshipAffect (linguistics)Quality (philosophy)Social psychologyDynamics (music)Communication

Abstract

fetched live from OpenAlex

This study explores the impact of electronic device usage on interpersonal relationships, analyzing both positive and negative consequences across diverse social dynamics. It highlights that while devices like smartphones facilitate communication and social connection, especially for isolated groups like the elderly and teenagers, they often negatively affect the quality of professional, intimate, and familial interactions. The concept of 'phubbing,' where attention is diverted to phones during social interactions, is critically examined for its role in reducing relationship satisfaction and emotional commitment. There are also some other concepts used with electronic devices that are discussed. Key mediating and moderating variables encompass individual characteristics and interpersonal perceptions. Practical insights for mitigating adverse effects and enhancing communication quality are provided. The study underscores the need for longitudinal research and varied measurement methods to capture the complex interplay between technology use and interpersonal relationship dynamics, aiming to guide future research toward a more profound understanding of these phenomena.

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.

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)0.006
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.368
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0060.003
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.404
GPT teacher head0.512
Teacher spread0.108 · 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