MétaCan
Menu
Back to cohort
Record W2146929761 · doi:10.1177/0956797610364119

Intention-Mediated Selective Helping in Infancy

2010· article· en· W2146929761 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

VenuePsychological Science · 2010
Typearticle
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsProsocial behaviorHelping behaviorPsychologyReciprocalSocial psychologyDevelopmental psychologySelection (genetic algorithm)Outcome (game theory)

Abstract

fetched live from OpenAlex

One way to maintain cooperation between unrelated individuals and decrease the chance of providing costly aid to those who will not reciprocate is by selectively helping on the basis of the content of previous interactions. In the present study, we sought to determine whether the earliest instances of human helping behavior show specificity. In three experiments, we found that infants preferred to help an individual who, in a previous interaction, intended to provide a toy over one who did not (Experiment 1) and that infants consider this positive intention even without a positive outcome (Experiment 2). Experiment 3 provided a more detailed examination of the basis of selection, suggesting that infants are not solely avoiding unwilling individuals, but also selectively helping those who have shown a willingness to provide. Taken together, these experiments indicate that early helping behaviors show characteristics of the rich reciprocal relationships observed in adult prosocial behavior.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.198
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.022
GPT teacher head0.357
Teacher spread0.335 · 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