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Record W2394620099 · doi:10.1111/cdev.12529

Unselective Overimitators: The Evolutionary Implications of Children's Indiscriminate Copying of Successful and Prestigious Models

2016· article· en· W2394620099 on OpenAlex
Maciej Chudek, Andrew Scott Baron, Susan Birch

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.

Bibliographic record

VenueChild Development · 2016
Typearticle
Languageen
FieldPsychology
TopicEvolutionary Psychology and Human Behavior
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCopyingBystander effectPsychologyDevelopmental psychologyAdaptive functioningCognitive psychologySocial psychology

Abstract

fetched live from OpenAlex

Children are both shrewd about whom to copy-they selectively learn from certain adults-and overimitators-they copy adults' obviously superfluous actions. Is overimitation also selective? Does selectivity change with age? In two experiments, 161 two- to seven-year-old children saw videos of one adult receiving better payoffs or more bystander attention than another. Children then watched the adults perform unnecessary actions on novel transparent devices. Children preferred the adult who received greater payoffs or bystander attention when asked questions like "Who do you think is smarter?" but overimitated both adults' unnecessary actions equally. Although older children overimitated more, unselectivity was consistent across ages. This pattern hints at a plausible adaptive function of overimitation: acquiring rarely demonstrated behaviors by practising them immediately.

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 score0.130
Threshold uncertainty score0.382

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 head0.026
GPT teacher head0.291
Teacher spread0.265 · 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