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Record W3094924050 · doi:10.5539/ijps.v12n4p19

Personality, Parental Behavior, and Attachment to Close Friends

2020· article· en· W3094924050 on OpenAlexvenueno aff
Tea Pavin Ivanec, Antonia Babojelić

Bibliographic record

VenueInternational Journal of Psychological Studies · 2020
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsAgreeablenessPsychologyExtraversion and introversionNeuroticismPersonalityDevelopmental psychologyBig Five personality traitsContext (archaeology)Hierarchical structure of the Big FiveFriendshipAttachment theorySocial psychology

Abstract

fetched live from OpenAlex

The aim of this study was to examine the relationship between young women’s personality traits, perceived parental behavior of their parents, and the dimensions of attachment to close friends. Results generally indicated significant effects of personality traits and parental behavior on attachment to close friends. More specifically, agreeableness was a negative predictor of attachment anxiety, and neuroticism was a positive predictor of the same attachment dimension. Both agreeableness and extraversion were negative predictors of attachment avoidance. Parental behavior was predictive for attachment avoidance in close friendship, while there were no effects of parental behavior on attachment anxiety. Mothers’ supportiveness and restrictive control were negative predictors of attachment avoidance, whereby fathers’ support was a positive predictor of this attachment dimension. The results imply the importance of both personality and parental behavior as determinants of attachment to close friends and also suggest the need for further research of specific associations within the context of these broad theoretical constructs.

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)0.003
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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.141
GPT teacher head0.523
Teacher spread0.382 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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