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Record W4287981271 · doi:10.1111/pere.12436

Back off: Disapproval of romantic relationships predicts closeness to disapproving network members

2022· article· en· W4287981271 on OpenAlexafffund
Sarah R. Gillian, Diane Holmberg, Kay Jenson, Karen L. Blair

Bibliographic record

VenuePersonal Relationships · 2022
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsTrent UniversityAcadia University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsClosenessPsychologySocial psychologyRomancePerspective (graphical)PerceptionDevelopmental psychology

Abstract

fetched live from OpenAlex

Abstract Is the perception that a social network member (SNM, i.e., friend or family member) disapproves of your romantic relationship associated with perceived changes in emotional closeness to that person? This question was investigated using an online survey ( N = 703). Participants reported their current closeness to a disapproving SNM, and retrospectively rated closeness before the disapproval and at the height of disapproval. As predicted, perceiving disapproval was associated with a drop in recalled emotional closeness to the SNM, with stronger disapproval associated with a steeper drop. Closeness recovered somewhat after the point of strongest disapproval, but not nearly to its original level. Analyses on a smaller sample of matched dyads ( N = 42) suggested this pattern was identical from the SNM's perspective. The recalled trajectory was moderated by SNM group (i.e., family/friend) and by relationship type (mixed‐sex/same‐sex, and age‐discrepant/similar‐age, but not mixed‐race/same‐race). We discuss implications for those in close relationships and their friends/family members.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.055
GPT teacher head0.340
Teacher spread0.285 · 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.

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

Citations8
Published2022
Admission routes2
Has abstractyes

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