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Record W2324814786 · doi:10.1080/15248372.2015.1058261

Source Monitoring and Executive Function in 2.5- to 3-Year-Olds

2016· article· en· W2324814786 on OpenAlexafffund
Suzanne Hala, Lee-Ann McKay, Alisha Brown, Valerie San Juan

Bibliographic record

VenueJournal of Cognition and Development · 2016
Typearticle
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Calgary
KeywordsPsychologyInhibitory controlRecallTask (project management)Developmental psychologyExecutive functionsCognitionWorking memoryVocabularyFunction (biology)Test (biology)Cognitive psychologyControl (management)Neuroscience

Abstract

fetched live from OpenAlex

Hala, Brown, McKay, and San Juan (2013) found that children as young as 2.5 years of age demonstrated high levels of accuracy when asked to recall whether they or the experimenter had carried out a particular action. In the research reported here, we examined the relation of early-emerging source monitoring to executive function abilities. Participants were children aged 2.5- to 3-years old. For the source-monitoring procedure, we used the Hala et al. (2013) task in which children and the experimenter took turns placing a total of 20 items on a model farm (encoding phase). For the source memory test, children were asked who had placed each item (retrieval phase). Executive function measures included assessments of working memory, delay-inhibitory control, and conflict-inhibitory control. The main finding was that inhibitory control measures were significantly related to performance on the source-monitoring task. This relation held for the conflict-inhibitory control measures even when controlling for age and vocabulary. The findings of this research suggest that even at the early age of 2.5 years, development of executive control is linked to the emergence of source-monitoring ability.

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 score0.430
Threshold uncertainty score0.130

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 head0.041
GPT teacher head0.277
Teacher spread0.236 · 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

Citations7
Published2016
Admission routes2
Has abstractyes

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