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Record W4401769354 · doi:10.62051/b49w7c87

The Impact of Social Media and Attachment Style in Long-Distance Intimate Overall Relationship Satisfaction and Conflict

2024· article· en· W4401769354 on OpenAlexaff
Yuying Yan

Bibliographic record

VenueTransactions on Social Science Education and Humanities Research · 2024
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsYork University
Fundersnot available
KeywordsStyle (visual arts)Attachment theoryPsychologySocial psychologySocial mediaPolitical scienceArtVisual arts

Abstract

fetched live from OpenAlex

Social media has become a prevalent channel for communication in the modern era. Long-distance couples must keep or improve their overall level of relationship satisfaction. Most earlier studies examined how an individual's attachment types and use of social networking sites (SNS) affect the evaluation of long-distance relationship satisfaction separately. there is insufficient data for identifying how satisfaction is affected when subjective (attachment styles) and objective (social media) factors are combined. This study aims to examine the shortcomings of past studies. According to this analysis, the couple's assessment of how satisfied they are with their relationship and their personal decisions made on social media are moderated by attachment style. Individuals with diverse attachment styles might disclose themselves in different ways, require varying degrees of intimacy, and view love relationships in various manners. Additionally, this article, including various methodological and hypothesis suggestions, will lay the groundwork for future research.

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)0.002
metaresearch head score (Gemma)0.011
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.123
GPT teacher head0.508
Teacher spread0.385 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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