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Record W2326185522 · doi:10.1111/cdep.12175

Evidence for Intuitive Morality: Preverbal Infants Make Sociomoral Evaluations

2016· article· en· W2326185522 on OpenAlexaff
Julia W. Van de Vondervoort, J. Kiley Hamlin

Bibliographic record

VenueChild Development Perspectives · 2016
Typearticle
Languageen
FieldNeuroscience
TopicPsychology of Moral and Emotional Judgment
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMoralityPsychologyIntuitionProsocial behaviorMoral developmentRationalitySocial cognitive theory of moralitySocial psychologyMoral reasoningMoral disengagementDevelopmental psychologyEpistemologyCognitive science

Abstract

fetched live from OpenAlex

Abstract Traditional views of morality and moral development rooted in rationality and demonstrations of explicit reasoning suggest that moral evaluations emerge in childhood. In contrast, definitions of morality rooted in intuition allow scholars to examine the emergence of moral evaluations among those who cannot reason this way, such as human infants. Consistent with an intuition-based view of morality, infants evaluate prosocial individuals positively and evaluate antisocial individuals negatively. These evaluations are sensitive to the intent and epistemic states of the person who is helping or hindering, and to the previous behavior of the person who is being helped or hindered. Early-emerging intuitions regarding others' morally relevant behaviors may have evolved to support wide-scale cooperation in human societies.

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)0.012
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.250
GPT teacher head0.389
Teacher spread0.139 · 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

Citations70
Published2016
Admission routes1
Has abstractyes

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