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Record W4411544705 · doi:10.1016/j.infbeh.2025.102099

The development of inductive reasoning during infancy

2025· article· en· W4411544705 on OpenAlexafffund
Anna E Baumann, Susan A. Graham

Bibliographic record

VenueInfant Behavior and Development · 2025
Typearticle
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Children's Hospital Foundation
KeywordsInductive reasoningSimilarity (geometry)Focus (optics)Cognitive developmentCognitionPsychologyInductive methodCognitive psychologyLogical reasoningCognitive scienceDevelopmental psychologyComputer scienceArtificial intelligenceMathematics education

Abstract

fetched live from OpenAlex

Category-based inductive reasoning involves assuming that members of the same category share common properties. This form of reasoning allows individuals to draw upon previous knowledge, enhancing cognitive efficiency. This review paper focuses on the advances made in research on category-based inductive reasoning over the past 25 years, with specific focus on infants between the ages of 12 and 36 months. Three key lines of research are reviewed: studies demonstrating the role of shape similarity in guiding inferences, studies examining the conditions under which infants rely on shared labels to guide their inferencing, and studies examining how generic language statements guide toddlers' inductive inferences. Finally, directions for future research are discussed, with particular focus on the need to examine the developmental origins of inductive reasoning in infants younger than 12 months.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
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 head0.016
GPT teacher head0.306
Teacher spread0.290 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2025
Admission routes2
Has abstractyes

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