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Record W2553252242 · doi:10.1111/cdev.12629

Nonrandom Acts of Kindness: Parasympathetic and Subjective Empathic Responses to Sadness Predict Children's Prosociality

2016· article· en· W2553252242 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChild Development · 2016
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsConcordia University
FundersNational Institute of Mental HealthCanadian Institutes of Health Research
KeywordsProsocial behaviorEmpathyPsychologySadnessVagal toneDevelopmental psychologyKindnessEmpathic concernFeelingAngerSocial psychologyPerspective-takingInternal medicineAutonomic nervous systemHeart rateMedicine

Abstract

fetched live from OpenAlex

How does empathic physiology unfold as a dynamic process, and which aspect of empathy predicts children's kindness? In response to empathy induction videos, 4- to 6-year-old children (N = 180) showed an average pattern of dynamic respiratory sinus arrhythmia (RSA) change characterized by early RSA suppression, followed by RSA recovery, and modest subsequent suppression during positive resolution of the empathic event. Children's capacity for this pattern of flexible RSA change was associated with their subjective empathic feelings, which were concurrently associated with more sympathetic and prosocial responses to others. Conversely, only children's dynamic RSA change longitudinally predicted prosocial behavior 2 years later. These findings have implications for understanding the dynamic and multifaceted nature of empathy, and its relation with prosocial development.

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)0.001
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 score0.132
Threshold uncertainty score0.882

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.017
GPT teacher head0.279
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