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Record W2149616849 · doi:10.1177/0956797615586402

Turbulent Times, Rocky Relationships

2015· article· en· W2149616849 on OpenAlexaff
Amanda L. Forest, David R. Kille, Joanne V. Wood, Lindsay R. Stehouwer

Bibliographic record

VenuePsychological Science · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicMedia Influence and Health
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPsychologyAffectionSocial psychologyInterpersonal relationshipPerceptionContext (archaeology)Interpersonal communicationRomanceSittingInterpersonal attractionDevelopmental psychologySocial relationAttraction

Abstract

fetched live from OpenAlex

What influences how people feel about and behave toward their romantic partners? Extending beyond features of the partners, relationship experiences, and social context, the current research examines whether benign, relationship-irrelevant factors-such as one's somatic experiences-can influence relationship perceptions and interpersonal behavior. Drawing on the embodiment literature, we propose that experiencing physical instability can undermine perceptions of relationship stability. Participants who experienced physical instability by sitting at a wobbly workstation rather than a stable workstation (Study 1), standing on one foot rather than two (Study 2), or sitting on an inflatable seat cushion rather than a rigid one (Study 3) perceived their romantic relationships to be less likely to last. Results were consistent with risk-regulation theory: Perceptions of relational instability were associated with reporting lower relationship quality (Studies 1-3) and expressing less affection toward the partner (Studies 2 and 3). These findings indicate that benign physical experiences can influence perceptions of relationship stability, exerting downstream effects on consequential relationship processes.

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)0.001
metaresearch head score (Gemma)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0060.003
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.318
GPT teacher head0.388
Teacher spread0.070 · 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

Citations49
Published2015
Admission routes1
Has abstractyes

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