MétaCan
Menu
Back to cohort
Record W3037787804 · doi:10.1177/1948550620929499

Lack of Intimacy Prospectively Predicts Breakup

2020· article· en· W3037787804 on OpenAlexafffund
Yoobin Park, Emily A. Impett, Stephanie S. Spielmann, Samantha Joel, Geoff MacDonald

Bibliographic record

VenueSocial Psychological and Personality Science · 2020
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsWestern UniversityUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyBreakupSocial psychologyLongitudinal studyPerceptionDevelopmental psychologyRomance

Abstract

fetched live from OpenAlex

In this prospective longitudinal study, we examined whether and how lack of intimacy or meaningful connection to a romantic partner (i.e., low social reward) and concerns over negative evaluation by the partner (i.e., high social threat) each predict dissolution of a relationship as well as adjustment when a breakup occurs. Our results showed that those who perceived lower levels of reward during the relationship were more likely to experience a breakup. This effect remained significant controlling for global relationship satisfaction and individual differences in attachment insecurity. The degree of reward also predicted experiencing less emotional attachment to the partner (now an ex-partner) postbreakup, but this effect diminished when controlling for satisfaction. In contrast, threat perceptions during the relationship did not predict breakup or emotional attachment to the ex. Our findings suggest that reward perceptions during the relationship have important consequences for relationship dissolution. Implications for breakup recovery are discussed.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.003
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 head0.181
GPT teacher head0.494
Teacher spread0.312 · 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

Citations10
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueSocial Psychological and Personality ScienceSame topicAttachment and Relationship DynamicsFrench-language works237,207