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Record W2606371035 · doi:10.1177/0265407517704721

Relationship satisfaction and the subjective distance of past relational events

2017· article· en· W2606371035 on OpenAlexafffund
Kassandra Cortes, Scott A. Leith, Anne E. Wilson

Bibliographic record

VenueJournal of Social and Personal Relationships · 2017
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsWilfrid Laurier UniversityUniversity of Waterloo
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsDistancingPsychologyPerceptionSocial psychologyReciprocalValence (chemistry)Context (archaeology)RomanceEvent (particle physics)Developmental psychologyCoronavirus disease 2019 (COVID-19)

Abstract

fetched live from OpenAlex

The present research examines how the subjective time of relational memories is linked to present relationship satisfaction. We tested the hypothesis that satisfied (but not dissatisfied) partners would keep happy relational events subjectively close in time and relegate transgressions to the subjectively distant past (regardless of when those events actually occurred). We found support for our predictions in the context of romantic relationships (Study 1) and with any type of close other (e.g., friends, family members; Study 2). To better understand the implications of the subjective distancing pattern among highly satisfied versus dissatisfied partners, we examined the role of perceptions of event importance. We found that highly satisfied partners’ adaptive pattern of distancing mediates their tendency to ascribe continued importance to past relationship glories, while dismissing earlier relational disappointments as unimportant (Study 2). We then examined the causal impact of subjective time on importance and on subsequent relationship satisfaction by manipulating both event valence and perceptions of subjective distance (Study 3). People were more satisfied when happy relational events felt close and unhappy ones felt distant. This work sheds light on a reciprocal process whereby highly satisfied partners navigate the temporal landscape of their relational histories by retaining and valuing happy memories and by discarding the relevance of painful ones, which then maintains or boosts subsequent relationship satisfaction.

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)0.001
metaresearch head score (Gemma)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.288
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.070
GPT teacher head0.383
Teacher spread0.313 · 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

Citations20
Published2017
Admission routes2
Has abstractyes

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