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Record W3134342022 · doi:10.1521/soco.2021.39.1.4

Connecting the Moral Core: Examining Moral Baby Research Through an Attachment Theory Perspective

2021· article· en· W3134342022 on OpenAlexaff
Audrey‐Ann Deneault, Stuart I. Hammond

Bibliographic record

VenueSocial Cognition · 2021
Typearticle
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPsychologyConstruct (python library)Perspective (graphical)MoralityEmbodied cognitionVitalityCore (optical fiber)Moral developmentSocial psychologySocial cognitive theory of moralityMoral disengagementCognitionAttachment theoryMeaning (existential)Moral behaviorDevelopmental psychologyEpistemologyPsychotherapist

Abstract

fetched live from OpenAlex

Infants care for and are cared for by others from early in life, a fact reflected in infants' morality and attachment. According to moral core researchers, infants are born with a moral sense that allows them to care about and evaluate the actions of third parties. In attachment theory, care manifests through infants' relationships with caregivers, which forms representations called internal working models that shape how babies think, feel, and act. Although accumulating evidence supports the existence of a moral core directed toward others, nevertheless, without a notion of care connected to infants' own lives, the core is an incomplete and underpowered construct. We show how the moral core, like attachment, could emerge in first- and second-person working models that develop through social interaction and incorporate representational forms (embodied, social, cognitive, emotional, moral), which contribute to the emergence of third-person representations and give infants' moral sense its vitality and meaning.

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)0.007
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.011
Scholarly communication0.0050.007
Open science0.0010.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.311
GPT teacher head0.467
Teacher spread0.156 · 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 designTheoretical or conceptual
Domainnot available
GenreReview

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

Citations9
Published2021
Admission routes1
Has abstractyes

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