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Record W2343175344 · doi:10.1037/dev0000127

Age-related differences in moral identity across adulthood.

2016· article· en· W2343175344 on OpenAlexafffund
Tobias Krettenauer, Lourdes Andrea Murua, Fanli Jia

Bibliographic record

VenueDevelopmental Psychology · 2016
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsWilfrid Laurier University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyConformityDevelopmental psychologyContext (archaeology)Adult developmentIdentity (music)PersonalityMoral developmentPersonality developmentSocial psychologyYoung adultPersonal identitySelf-concept

Abstract

fetched live from OpenAlex

In this study, age-related differences in adults' moral identity were investigated. Moral identity was conceptualized a context-dependent self-structure that becomes differentiated and (re)integrated in the course of development and that involves a broad range of value-orientations. Based on a cross-sectional sample of 252 participants aged 14 to 65 years (148 women, M = 33.5 years, SD = 16.9) and a modification of the Good Self-Assessment, it was demonstrated that mean-level of moral identity (averaged across the contexts of family, school/work, and community) significantly increased in the adult years, whereas cross-context differentiation showed a nonlinear trend peaking at the age of 25 years. Value-orientations that define individuals' moral identity shifted so that self-direction and rule-conformity became more important with age. Age-related differences in moral identity were associated with, but not fully attributable to changes in personality traits. Overall, findings suggest that moral identity development is a lifelong process that starts in adolescence but expands well into middle age. (PsycINFO Database Record

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)0.001
metaresearch head score (Gemma)0.005
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
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.131
GPT teacher head0.419
Teacher spread0.288 · 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

Citations59
Published2016
Admission routes2
Has abstractyes

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