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Record W4409726729 · doi:10.1080/15248372.2025.2492021

That’s not the One I Wanted: Feedback Improves 5-Year-olds’ Communicative Perspective-Taking

2025· article· en· W4409726729 on OpenAlexaffabout
Narae Ju, Valerie San Juan, Elizabeth S. Nilsen, Susan A. Graham

Bibliographic record

VenueJournal of Cognition and Development · 2025
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversity of WaterlooUniversity of Calgary
Fundersnot available
KeywordsPsychologyPerspective (graphical)Perspective-takingCommunicative competenceDevelopmental psychologyCognitive psychologySocial psychologyPedagogyEmpathy

Abstract

fetched live from OpenAlex

Effective communication requires participants to recognize what knowledge is shared and what knowledge remains unique to each person. Although research has examined the developmental emergence of this communicative skill, it is unclear how children’s attention to shared knowledge is impacted by corrective feedback. Constraint-based models of language processing suggest that listeners simultaneously consider and weigh cues during language comprehension; however, it is unclear to what extent (and when) children use feedback from a communicative partner, relative to other salient cues such as linguistic match, during comprehension. This study addresses this gap by examining whether corrective feedback affects the time course and outcome of Canadian 5-year-olds’ (n = 64) use of shared knowledge to guide interpretation of a speaker’s referential intent. Children who received feedback on the accuracy of their interpretations pointed to target objects more than those who did not receive feedback. Children in the feedback group showed preferential looking toward the target (relative to a competitor), with this effect emerging at later stages of sentence processing. Children’s working memory capacity was positively associated with greater fixation on the target object during trials that required perspective-taking, only if they had received feedback on their previous choices.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.753
Threshold uncertainty score0.390

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.057
GPT teacher head0.342
Teacher spread0.286 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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