CoChat
Sign Up
Cited by 126Child and Animal Learning DevelopmentBayesian Modeling and Causal InferenceCategorization, perception, and language

Rational variability in children's causal inferences: the sampling hypothesis

Denison, Stephanie, Bonawitz, Elizabeth, Gopnik, Alison, Griffiths, Thomas L.·2013·Cognition
DOI 10.1016/j.cognition.2012.10.010

Published version of a preprint

Open this paper in CoChat — free account

Abstract

We present a proposal-"The Sampling Hypothesis"-suggesting that the variability in young children's responses may be part of a rational strategy for inductive inference. In particular, we argue that young learners may be randomly sampling from the set of possible hypotheses that explain the observed data, producing different hypotheses with frequencies that reflect their subjective probability. We test the Sampling Hypothesis with four experiments on 4- and 5-year-olds. In these experiments, children saw a distribution of colored blocks and an event involving one of these blocks. In the first experiment, one block fell randomly and invisibly into a machine, and children made multiple guesses about the color of the block, either immediately or after a 1-week delay. The distribution of guesses was consistent with the distribution of block colors, and the dependence between guesses decreased as a function of the time between guesses. In Experiments 2 and 3 the probability of different colors was systematically varied by condition. Preschoolers' guesses tracked the probabilities of the colors, as should be the case if they are sampling from the set of possible explanatory hypotheses. Experiment 4 used a more complicated two-step process to randomly select a block and found that the distribution of children's guesses matched the probabilities resulting from this process rather than the overall frequency of different colors. This suggests that the children's probability matching reflects sophisticated probabilistic inferences and is not merely the result of a naïve tabulation of frequencies. Taken together the four experiments provide support for the Sampling Hypothesis, and the idea that there may be a rational explanation for the variability of children's responses in domains like causal inference.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.cognition.2012.10.010

Cites

61 of 61 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Bayesian samplers can match behavioral stochasticity in tasks such as perception, categorization, causal reasoning, and decision making.

    “Bayesian samplers can match behavioral stochasticity in tasks such as perception, categorization, causal reasoning, and decision making [20,21,23,24].”

    From Bayesian Brains without Probabilities (2016) · cites this paper as [24]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 3

  1. Galton, F. (1907). Vox Populi. Nature , 75 (1949), 450-451.
  2. Seth, A.K. (2011). Optimal agent-based models of action selection. In Modeling Natural Action Selection. A.K. Seth, T.J. Prescott, and J.J. Bryson (Eds). Cambridge University Press.
  3. Stephens, D. W., & Krebs, J. R. (1986). Foraging theory . Princeton, NJ: Princeton University Press.

Cited by

Sorted by citations

Related

Authors
Denison, S., Bonawitz, E., Gopnik, A., & Griffiths, T. L.
Affiliations
  • University of Waterloo (CA)
  • University of California, Berkeley (US)
Corresponding author
Denison, Stephanie
ORCID
Venue
Cognition
Publisher
Elsevier BV
Published
2013-02
Volume
126
Issue
2
Pages
285-300
ISSN
0010-0277 (ISSN-L)
DOI
10.1016/j.cognition.2012.10.010
OpenAlex
W2120212072
Cited by
126
References
61
Citations by year
2026: 3 · 2025: 6 · 2024: 15 · 2023: 9 · 2022: 8 · 2021: 6 · 2020: 11 · 2019: 9 · 2018: 15 · 2017: 16 · 2016: 7 · 2015: 12 · 2014: 7 · 2013: 2
FWCI
13.46
Type
journal article
Language
en
Open access
closed
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations
  • Cognition (publishedVersion)
  • PubMed (publishedVersion)
  • Rutgers University Community Repository (Rutgers University) (submittedVersion)
  • UWA Profiles and Research Repository (UWA) (submittedVersion)
Topics
  • Social Sciences › Psychology › Developmental and Educational Psychology › Child and Animal Learning Development
  • Physical Sciences › Computer Science › Artificial Intelligence › Bayesian Modeling and Causal Inference
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Categorization, perception, and language
Keywords
causal inference, inductive reasoning, probability matching, preschool children, probabilistic reasoning, response variability, random sampling, subjective probability
MeSH terms
Child Development, Child, Preschool, Cognition, Concept Formation, Female, Humans, Male, Probability Learning, Problem Solving

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review