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Record W2159638062 · doi:10.1017/s0305000907008392

Developing spatial localization abilities and children's interpretation of<i>where</i>

2008· article· en· W2159638062 on OpenAlexaff
Elena Nicoladis, Edward H. Cornell, Melissa Gates

Bibliographic record

VenueJournal of Child Language · 2008
Typearticle
Languageen
FieldEngineering
TopicSpatial Cognition and Navigation
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPsychologyInterpretation (philosophy)Cognitive psychologySpatial abilityLinguisticsDevelopmental psychologyCognition

Abstract

fetched live from OpenAlex

Two-year-old children often start asking questions with where. In this study we test whether children understand where to mean route or absolute location and whether the size of the space or elevation made a difference. Previous research has documented developmental changes over the preschool years in children's non-verbal spatial reasoning. Forty-eight children between two and five years of age were interviewed. We asked them to point in response to where questions about an object, rooms on the same floor and on a different floor. All children pointed to the location of the hidden objects. The youngest children pointed to the route to rooms while the oldest children were more likely to point to the location of rooms. With age, the children gradually used more spatial location terms than deictic terms in response to where. These results suggest that children's meaning of where initially differs for different sized spaces and developmental changes reflect non-verbal 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.002
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.004
GPT teacher head0.204
Teacher spread0.200 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2008
Admission routes1
Has abstractyes

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