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Record W2640692887 · doi:10.1002/dev.21535

A new approach to measuring patience in preschoolers

2017· article· en· W2640692887 on OpenAlexafffund
Gladys Barragan‐Jason, Cristina M. Atance

Bibliographic record

VenueDevelopmental Psychobiology · 2017
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaAgence Nationale de la RechercheVedecká Grantová Agentúra MŠVVaŠ SR a SAVGovernment of Ontario
KeywordsPatienceGratificationPsychologyCognitionDevelopmental psychologyTask (project management)Delay of gratificationCognitive psychologySocial psychologyNeuroscience

Abstract

fetched live from OpenAlex

Patience in children has usually been studied using delay of gratification paradigms. However, another important aspect of patience that has not been well documented is the ability to adjust one's behavior while waiting without an explicit reward as a motivator (e.g., sitting in the doctor's waiting room). To examine this aspect of patience, video-recordings of sixty-one 3- and 4-year olds waiting for two separate 3-min periods were examined and coded for children's spontaneous behaviors. We found that 4-year olds displayed more patient (i.e., staying still) behaviors than 3-year olds during this "waiting paradigm." Interestingly, we also found that children who displayed less patient behaviors during the waiting paradigm were also those who succeeded on a future-thinking task. These findings have important implications for measuring patience in young children and highlight the potential impact of spontaneous behaviors on children's performance in cognitive tasks such as those assessing future-oriented cognition.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.733

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.234
GPT teacher head0.344
Teacher spread0.110 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations5
Published2017
Admission routes2
Has abstractyes

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