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Record W2772349952 · doi:10.51657/ric.v4i1.40996

Lev Vygotsky: From Theator to Psychology

2017· article· en· W2772349952 on OpenAlexvenueno aff
В.С. Собкин

Bibliographic record

VenueRevue internationale du CRIRES innover dans la tradition de Vygotsky · 2017
Typearticle
Languageen
FieldComputer Science
TopicEducational Methods and Teacher Development
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)DramaZone of proximal developmentPsychologyPerceptionExpression (computer science)Period (music)CriticismReincarnationEpistemologyAestheticsVisual artsLiteratureArtHistoryDevelopmental psychologyComputer science

Abstract

fetched live from OpenAlex

The article presents the analysis of L. S. Vygotsky’s works dedicated to the theater arts and is organized according Vygotsky’s di˙erent life and work stages. Meanwhile, special attention is paid to the Gomel period during which a large number of reviews were written by Vygotsky and publishe in “Nash ponedel’nik” and “Polesskaia pravda” newspapers. It is shown that even at the beginning of his work, he was interested not only in a range of problems in art, but also psychological problems related to art perception and creativeness. Vygotsky’s usage of structural concept ideas about the peculiar properties of literary text composition are also explored. Vygotsky analyzes the socio- psychological mechanisms of theatrical art e˙ect. Furthermore, those areas which are widely used by Vygotsky in determining the characteristics of cast reincarnation are examined. Special emphasis is placed on the di˙erent elements of the actor techniques (speech, movement, emotional expression, acting personality and etc.). Materials are widely used in this study and help identify the socio- cultural context that defined Vygotsky’s values at di˙erent stages of his work, related to his drama criticism and his formation as a professional psychologist.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0040.012
Scholarly communication0.0060.004
Open science0.0010.003
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.061
GPT teacher head0.344
Teacher spread0.283 · 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 designTheoretical or conceptual
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
Published2017
Admission routes1
Has abstractyes

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