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Record W2906118139 · doi:10.1037/dev0000661

Distant lands make for distant possibilities: Children view improbable events as more possible in far-away locations.

2018· article· en· W2906118139 on OpenAlexafffund
Celina K. Bowman‐Smith, Andrew Shtulman, Ori Friedman

Bibliographic record

VenueDevelopmental Psychology · 2018
Typearticle
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPsychologyContext (archaeology)Event (particle physics)Social psychologyLocationDevelopmental psychologyCognitive psychologyHistoryGeography

Abstract

fetched live from OpenAlex

= 300) might have more success in recognizing that these events are possible if they considered whether the events could happen in a distant country. Children heard about improbable and impossible events (Experiments 1A, 1B, and 2) and about ordinary events (Experiment 2) and either judged whether the events could happen in a distant country or locally (Experiments 1A and 2) or with their location unspecified (Experiment 1B). Children were more likely to judge that extraordinary events could happen in a distant country than when the same events were described locally or with location unspecified; also, older children were more likely to deny these events could happen when they were local compared with when their location was unspecified. We also found some evidence that manipulating distance affects judgments more strongly for improbable events than for impossible one. Together, the findings show that children's assessments of whether hypothetical events are possible are affected by the geographic context of the events. The findings are consistent with accounts holding that children normally assess whether hypothetical events are possible by drawing on their knowledge of the ordinary world but further suggest that children modify this approach when considering events in distant lands. (PsycINFO Database Record (c) 2019 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 score0.076
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0020.001

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 head0.020
GPT teacher head0.346
Teacher spread0.326 · 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

Citations28
Published2018
Admission routes2
Has abstractyes

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