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Record W2791810961 · doi:10.1177/0146167218760800

Are Children Perceived to Be Morally Exceptional? Different Sets of Psychological Variables Predict Adults’ Moral Judgments About Adults and Young Children

2018· article· en· W2791810961 on OpenAlexafffund
Cindel White, Mark Schaller

Bibliographic record

VenuePersonality and Social Psychology Bulletin · 2018
Typearticle
Languageen
FieldNeuroscience
TopicPsychology of Moral and Emotional Judgment
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologySocial psychologyIntentionalityDevelopmental psychologyMoral developmentMoral disengagementCognitionMorality

Abstract

fetched live from OpenAlex

Conceptual analyses of moral cognition suggest that different variables may influence moral judgments depending upon the target's age. Five experiments (total N = 1,733) tested the implications for moral judgments about adults and young children. Results show that adults who were perceived to be more cognitively capable were judged to have greater moral rights and their transgressions were judged less harshly, but young children who were perceived to be more cognitively capable were judged to have fewer moral rights and their transgressions were judged more harshly. In addition, the perceived intentionality and disgustingness of transgressions had weaker effects on judgments about child transgressors than about adult transgressors. Perceivers' care-giving motives also had diverging effects on moral judgments, predicting more lenient judgments about children's transgressions and harsher judgments about adults' transgressions. These results have novel implications-both conceptual and practical-for moral judgments regarding adults and children.

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)0.006
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.076
GPT teacher head0.317
Teacher spread0.242 · 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

Citations12
Published2018
Admission routes2
Has abstractyes

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