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Record W3108106016 · doi:10.1111/pere.12360

Association between attachment insecurity and couple adjustment: Moderation by couple memory networks

2020· article· en· W3108106016 on OpenAlexafffund
Alexandre Lejeune, Nabil Bouizegarene, Frédérick L. Philippe

Bibliographic record

VenuePersonal Relationships · 2020
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsUniversité du Québec à Montréal
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyAssociation (psychology)ModerationDevelopmental psychologyCognitionAnxietySocial psychologyCognitive psychologyPsychotherapist

Abstract

fetched live from OpenAlex

Abstract This study investigated whether couple‐related memories and their organization in memory networks could act as cognitive resources to protect against the negative impact of insecure attachment on couple adjustment. In two studies ( n 1 = 153, n 2 = 567), participants in a romantic relationship described a significant couple‐related memory and provided networked memories associated with their couple‐related memory, to assess its organization in the memory system, and rated each memory for its level of need satisfaction. Findings across the two studies revealed significant moderations of need satisfaction in couple‐related memory networks, such that a higher level of satisfaction need within couple‐related memory networks was associated with a reduced negative association of attachment anxiety and avoidance with couple adjustment. When examined separately, it was shown that need‐satisfying networked memories, but not main couple‐related memories, moderated the negative association of insecure attachment with couple adjustment.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.345
Threshold uncertainty score0.943

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 studies0.0010.000
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 head0.047
GPT teacher head0.333
Teacher spread0.286 · 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.

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

Citations5
Published2020
Admission routes2
Has abstractyes

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