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Record W4388734813 · doi:10.1037/dev0001670

Improbable but possible: Training children to accept the possibility of unusual events.

2023· article· en· W4388734813 on OpenAlexaff
Andrew Shtulman, Brandon W. Goulding, Ori Friedman

Bibliographic record

VenueDevelopmental Psychology · 2023
Typearticle
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsUniversity of WaterlooUniversity of Winnipeg
FundersJames S. McDonnell Foundation
KeywordsPsychologyPsycINFOCausality (physics)CognitionSimilarity (geometry)Event (particle physics)Developmental psychologyCognitive developmentCognitive psychologySocial psychologyMEDLINE

Abstract

fetched live from OpenAlex

= 128) to consider either the similarity between the target event and unusual events that have actually occurred or causal mechanisms that might bring the target event about. Both trainings increased children's acceptance of improbable events but only for the types of events addressed during training. Older children were more likely to accept improbable events, as were children who scored higher on a measure of cognitive reflection, but neither age nor cognitive reflection moderated the effects of training. These findings indicate that children can use both similarity and causality to assess possibility, but the use of this information is highly circumscribed, further demonstrating how robustly children conflate improbability with impossibility. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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 score0.334
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.003

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 head0.060
GPT teacher head0.361
Teacher spread0.302 · 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; both teacher heads agree on what is shown here.

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

Citations9
Published2023
Admission routes1
Has abstractyes

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