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Record W4388052456 · doi:10.1162/opmi_a_00110

What’s in the Box? Preschoolers Consider Ambiguity, Expected Value, and Information for Future Decisions in Explore-Exploit Tasks

2023· article· en· W4388052456 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.

Bibliographic record

VenueOpen Mind · 2023
Typearticle
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsUniversity of Waterloo
FundersJacobs FoundationJames S. McDonnell Foundation
KeywordsExploitAmbiguityContext (archaeology)Value (mathematics)Order (exchange)Computer sciencePsychologyCognitive psychologyEconomicsMachine learningComputer security

Abstract

fetched live from OpenAlex

Self-directed exploration in childhood appears driven by a desire to resolve uncertainties in order to learn more about the world. However, in adult decision-making, the choice to explore new information rather than exploit what is already known takes many factors beyond uncertainty (such as expected utilities and costs) into account. The evidence for whether young children are sensitive to complex, contextual factors in making exploration decisions is limited and mixed. Here, we investigate whether modifying uncertain options influences explore-exploit behavior in preschool-aged children (48-68 months). Over the course of three experiments, we manipulate uncertain options' ambiguity, expected value, and potential to improve epistemic state for future exploration in a novel forced-choice design. We find evidence that young children are influenced by each of these factors, suggesting that early, self-directed exploration involves sophisticated, context-sensitive decision-making under uncertainty.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.573
Threshold uncertainty score0.501

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 communication0.0000.001
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 head0.093
GPT teacher head0.374
Teacher spread0.281 · 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