MétaCan
Menu
Back to cohort
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 (n1 = 153, n2 = 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 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)0.002
metaresearch head score (Gemma)0.010
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
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 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

Citations5
Published2020
Admission routes2
Has abstractyes

Explore more

Same venuePersonal RelationshipsSame topicAttachment and Relationship DynamicsFrench-language works237,207