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Record W2045573192 · doi:10.1002/cd.273

Moral emotions and moral judgments in children's narratives: Comparing real-life and hypothetical transgressions

2010· article· en· W2045573192 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNew Directions for Child and Adolescent Development · 2010
Typearticle
Languageen
FieldPsychology
TopicEmotions and Moral Behavior
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychologyNarrativeMoral developmentSocial psychologyInterpersonal communicationContext (archaeology)Meaning (existential)CognitionSocial cognitive theory of moralityMoral reasoningSocial cognitionDevelopmental psychology

Abstract

fetched live from OpenAlex

How children make meaning of their own social experiences in situations involving moral issues is central to their subsequent affective and cognitive moral learning. Our study of young children's narratives describing their interpersonal conflicts shows that the emotions and judgments constructed in the course of these real-life narratives differ from the emotions and judgments generated in the context of hypothetical transgressions. In the narratives, all emotions mentioned spontaneously were negative. In contrast, emotions attributed in the interview part covered a broader spectrum. One's own real-life transgressions were judged less severe and more justified than hypothetical transgressions.

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.

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)0.000
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 score0.061
Threshold uncertainty score0.838

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.040
GPT teacher head0.303
Teacher spread0.262 · 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