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Record W1557920161 · doi:10.1111/pere.12015

Relationship quality promotes the desire for closeness among distressed avoidantly attached individuals

2013· article· en· W1557920161 on OpenAlexaff
Erica B. Slotter, Laura B. Luchies

Bibliographic record

VenuePersonal Relationships · 2013
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsRedeemer University
Fundersnot available
KeywordsClosenessPsychologyDistressSocial psychologyRomanceQuality (philosophy)Developmental psychologySocial relationshipClinical psychologyPsychoanalysis

Abstract

fetched live from OpenAlex

Abstract Individuals who experience attachment avoidance tend to desire less closeness in their romantic relationships than others, especially when experiencing distress. However, emerging research suggests that avoidant individuals value social closeness and are more comfortable with it when they perceive that seeking closeness is welcomed. Thus, this research examined the relationship characteristics that might predict avoidant individuals seeking more closeness than they would otherwise. We investigated whether perceiving their relationship to be high quality would predict avoidant individuals desiring more closeness when distressed. We hypothesized that avoidant individuals who perceived their relationship to be high quality would desire greater closeness with their partners when distressed—counteracting their tendency to eschew relational closeness. A study of dating couples supported this hypothesis.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.124
GPT teacher head0.416
Teacher spread0.292 · 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

Citations71
Published2013
Admission routes1
Has abstractyes

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