MétaCan
Menu
Back to cohort
Record W2899775761 · doi:10.1038/s41467-018-07138-5

Early childhood investment impacts social decision-making four decades later

2018· article· en· W2899775761 on OpenAlexafffund
Yi Luo, Sébastien Hétu, Terry Lohrenz, Andreas Hula, Peter Dayan, Sharon Landesman Ramey, Libbie Sonnier‐Netto, Jonathan Lisinski, Stephen M. LaConte, Tobias Nolte, Peter Fonagy, Elham Rahmani, P. Read Montague, Craig T. Ramey

Bibliographic record

VenueNature Communications · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsUniversité de Montréal
FundersCanadian Institutes of Health ResearchBarts Health NHS TrustNational Institute for Health and Care ResearchGatsby Charitable FoundationWellcome Trust
KeywordsUltimatum gamePsychological interventionEnforcementInvestment (military)PsychologyInvestment decisionsEarly childhoodCognitionSocial decision makingEconomicsPublic economicsDevelopmental psychologySocial psychologyBehavioral economicsMicroeconomicsPolitical sciencePsychiatry

Abstract

fetched live from OpenAlex

Early childhood educational investment produces positive effects on cognitive and non-cognitive skills, health, and socio-economic success. However, the effects of such interventions on social decision-making later in life are unknown. We recalled participants from one of the oldest randomized controlled studies of early childhood investment-the Abecedarian Project (ABC)-to participate in well-validated interactive economic games that probe social norm enforcement and planning. We show that in a repeated-play ultimatum game, ABC participants who received high-quality early interventions strongly reject unequal division of money across players (disadvantageous or advantageous) even at significant cost to themselves. Using a multi-round trust game and computational modeling of social exchange, we show that the same intervention participants also plan further into the future. These findings suggest that high quality early childhood investment can result in long-term changes in social decision-making and promote social norm enforcement in order to reap future benefits.

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 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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.693
Threshold uncertainty score0.999

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 studies0.0030.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.029
GPT teacher head0.367
Teacher spread0.338 · 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 teacher head, not a consensus.

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

Citations30
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueNature CommunicationsSame topicEarly Childhood Education and DevelopmentFrench-language works237,207