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Record W2581834243 · doi:10.17759/chp.2015110310

Representation of Objective Situations in Preschool Children

2015· article· en· W2581834243 on OpenAlexaff
Nikolay Veraksa

Bibliographic record

VenueCultural-Historical Psychology · 2015
Typearticle
Languageen
FieldPsychology
TopicPsychology of Development and Education
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsNormativeCategorizationRepresentation (politics)CognitionDialecticPsychologyCognitive psychologySign (mathematics)Subject (documents)MediationTransformation (genetics)Symbolic communicationOrientation (vector space)Computer scienceCognitive scienceArtificial intelligenceEpistemologyMathematicsSociologyLinguistics

Abstract

fetched live from OpenAlex

The paper focuses on the types of representations of objective situations, that is, situations which are defined independently of the subject, by certain external perceptible circumstances and social expectations or rules. The author distinguishes between three types of objective situations in which children act: normative, developing and ambiguous. For each of these types there is a corresponding form of representation: sign, dialectical and symbolic. Each form is a product of the subject's cognitive activity, at the core of which lie cognitive abilities — a system of culturally specific means and ways of using them. The paper outlines normative and stabilizing abilities, transformation abilities, and symbolic mediation abilities. They help categorize different objects and features, enable transformation of situations and provide possibilities for orientation in ambiguous situations.

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)0.001
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.003
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.118
GPT teacher head0.422
Teacher spread0.304 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

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