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Record W2686566212 · doi:10.1111/mbe.12142

Children's Enactment of Characters' Movements: A Novel Measure of Spatial Situation Model Representations and Indicator of Comprehension

2017· article· en· W2686566212 on OpenAlexaff
Angela Nyhout, Daniela K. O’Neill

Bibliographic record

VenueMind Brain and Education · 2017
Typearticle
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComprehensionRepresentation (politics)Task (project management)Character (mathematics)NarrativeVocabularyMovement (music)PsychologyCognitive psychologySpace (punctuation)Active listeningLinguisticsComputer scienceCommunicationAestheticsArtMathematicsPoliticsPolitical scienceEngineering

Abstract

fetched live from OpenAlex

ABSTRACT A story's space or setting often determines and constrains the actions of its characters. We report on an experiment with 106 children of 7–8 years old in which, using a novel enactment task, we measured children's representation of a story character's movement during story listening. We found that children were more likely to enact movements that were explicitly stated in the passage than those they had to infer based on their situation model representation of the house and the character's location within it. We found that this ability to infer movements was significantly predictive of children's narrative comprehension after controlling for oral comprehension, vocabulary, working memory, and enactment of explicitly stated movements. We discuss the role of spatial situation models in comprehension and potential future uses for this enactment task in research and classrooms.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.416
Threshold uncertainty score0.264

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 head0.318
Teacher spread0.292 · 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 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

Citations8
Published2017
Admission routes1
Has abstractyes

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