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Adolescent Naturalistic Conceptions of Moral Maturity

2011· article· en· W1876411091 on OpenAlexaff
Sam A. Hardy, Lawrence J. Walker, Joseph A. Olsen, Jonathan E. Skalski, Jason C. Basinger

Bibliographic record

VenueSocial Development · 2011
Typearticle
Languageen
FieldNeuroscience
TopicPsychology of Moral and Emotional Judgment
Canadian institutionsUniversity of British Columbia
FundersUniversity of PittsburghUniversity of Minnesota
KeywordsPsychologyMaturity (psychological)Moral developmentMoralitySocial cognitive theory of moralityDevelopmental psychologySimilarity (geometry)Moral disengagementSocial psychologySet (abstract data type)Moral reasoningMoral psychologyEpistemology

Abstract

fetched live from OpenAlex

Abstract Understanding lay conceptions of morality is important not only because they can guide moral psychology theory but also because they may play a role in everyday moral functioning. Thus, the purpose of this study was to examine adolescent conceptions of moral maturity. Study 1 (200 adolescents 12–18 years) involved a free‐listing procedure to generate traits descriptive of a moral person. In Study 2, involving 100 early (11–14 years) and 99 late (15–18 years) adolescents, the moral person traits obtained in the first study were rated in terms of how well they described a moral person. Study 3, with 234 early (10–14 years) and 240 late (15–18 years) adolescents, entailed a similarity‐sorting task and a rating procedure similar to that from Study 2. This set of studies uncovered early and late adolescents' implicit typologies of moral maturity and pointed to possible age similarities and differences.

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)0.006
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 score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.281
GPT teacher head0.304
Teacher spread0.023 · 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

Citations30
Published2011
Admission routes1
Has abstractyes

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