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Record W3101354859 · doi:10.1037/pspp0000367

Facet-level personality development in the transition to adolescence: Maturity, disruption, and gender differences.

2020· article· en· W3101354859 on OpenAlexfundno aff
Cassandra M Brandes, Shauna C. Kushner, Kathrin Herzhoff, Jennifer L. Tackett

Bibliographic record

VenueJournal of Personality and Social Psychology · 2020
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyFacet (psychology)PersonalityAgreeablenessBig Five personality traitsDevelopmental psychologyExtraversion and introversionConscientiousnessOpenness to experienceNeuroticismPersonality developmentLatent growth modelingTraitSocial psychology

Abstract

fetched live from OpenAlex

= 0.84). Results of latent growth curve models showed substantial facet-level personality stability in this period, as well as small to moderate linear change in 13 of 15 facets. Gender differences in change were evident for 9 facets. Overall patterns suggested consistent increases in agreeableness facets with null to small gender differences. Neuroticism and openness to experience facet change was heterogeneous within each domain, but patterns were similar for boys and girls. Extraversion primarily decreased, though the magnitude and direction of change differed between facets and genders. Conscientiousness increased across all facets, but only among girls. These findings overall demonstrate a high degree of developmental consistency in facets within each domain as well as some notable differences. Further, this study contributes to a small and somewhat mixed evidence base for current theories of adolescent personality development. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.837
Threshold uncertainty score0.760

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.141
GPT teacher head0.381
Teacher spread0.240 · 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

Citations45
Published2020
Admission routes1
Has abstractyes

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