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Record W2883685044 · doi:10.1080/15248372.2018.1495219

Savvy or Haphazard? Comparing Preschoolers’ Performance Across Selective Learning Tasks Based on Different Epistemic Indicators

2018· article· en· W2883685044 on OpenAlex
Patricia É. Brosseau-Liard, Alana Iannuzziello, Jade Varin

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Cognition and Development · 2018
Typearticle
Languageen
FieldPsychology
TopicEducational Strategies and Epistemologies
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPsychologyCognitive psychologyFunction (biology)Concept learningRelation (database)CognitionConceptual changeReliability (semiconductor)Developmental psychologyMathematics educationPower (physics)Computer science

Abstract

fetched live from OpenAlex

Children frequently select learning sources based on epistemic cues, or cues pertaining to informants’ knowledge. Previous research has shown that preschoolers preferentially learn from informants who have been accurate in the past, appear confident, or have had visual access to relevant information. The present series of studies aimed to investigate the relation between these 3 types of epistemic selective learning abilities in 176 children ages 3 years to 6 years. Results indicated that children’s performance was mostly uncorrelated across the different selective learning tasks and tasks measuring theory of mind and executive function were not found to predict any selective learning skills. Implications for the reliability and current conceptual understanding of these selective learning tasks are discussed.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score0.370

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.055
GPT teacher head0.344
Teacher spread0.289 · 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