MétaCan
Menu
Back to cohort
Record W2977082306 · doi:10.3390/socsci8100271

Reciprocal Personality Assessment of Both Partners in a Romantic Relationship and Its Correlates to Dyadic Adjustment

2019· article· en· W2977082306 on OpenAlexafffund
Evelyne Smith, Adèle Guérard, Hugues Leduc, Ghassan El‐Baalbaki

Bibliographic record

VenueSocial Sciences · 2019
Typearticle
Languageen
FieldPsychology
TopicPersonality Traits and Psychology
Canadian institutionsUniversité du Québec à Montréal
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyPersonalityPartner effectsBig Five personality traitsPersonality Assessment InventorySocial psychologyAgreeablenessDevelopmental psychologyPerceptionExtraversion and introversion

Abstract

fetched live from OpenAlex

This project examines the effects of self- and partner-rated personality and their reciprocal interaction between two partners. Personality in 113 young dating couples was measured with the Five-Factor Model and maladaptive personality trait model of the DSM-5. Partners completed self- and partner-reports of the NEO-FFI-3 and the Personality Inventory for DSM-5 (PID-5) as well as the self-report Dyadic Adjustment Scale (DAS). Three sets of Actor-Partner Interdependence Models (APIMs) were run to estimate actor and partner effects of self-rated personality, partner-rated personality, and of both sets of effects simultaneously in an integrated model. When self- and partner-rating models were examined separately, several significant actor and partner effects were observed. However, the strongest effects were observed in the partner-rating models. When self- and partner-rated personality were examined at the same time, most effects from the self-rating models disappeared. Furthermore, most of the effects as well as the strongest one observed were associated with an individual’s perception of their partner’s personality, particularly men’s perception of women’s personality. This study demonstrates the incremental predictive utility of individuals’ perception of their partner’s personality for explaining their own dyadic 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 score0.170
Threshold uncertainty score0.766

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.114
GPT teacher head0.458
Teacher spread0.344 · 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

Citations3
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueSocial SciencesSame topicPersonality Traits and PsychologyFrench-language works237,207