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Record W2014285392 · doi:10.1037/1093-4510.11.2.101

Rethinking the early history of post-Vygotskian psychology: The case of the Kharkov school.

2008· article· en· W2014285392 on OpenAlexaff
Anton Yasnitsky, Michel Ferrari

Bibliographic record

VenueHistory of Psychology · 2008
Typearticle
Languageen
FieldPsychology
TopicAcademic and Historical Perspectives in Psychology
Canadian institutionsInstitute for Christian Studies
Fundersnot available
KeywordsHistory of psychologyPsychologyActivity theoryConsciousnessZone of proximal developmentPedagogyCognitive psychology

Abstract

fetched live from OpenAlex

Between the death of Vygotsky in 1934 and the discovery of Vygotsky's work in the West in 1962, Vygotskian psychology was developed through research done by the first generation of Vygotsky's students and their followers, primarily associated with the Kharkov School. Surprisingly, these studies carried out in the 1930s, of great importance for the development of virtually all subsequent Vygotskian psychology, still remain largely unknown; this represents a significant gap in understanding the history of Vygotskian psychology as an empirical study of consciousness. This paper provides a systematic overview of the research agenda of the Kharkov group between 1931 and 1941 and provides new insights into the early development of Vygotskian psychology.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0130.037
Scholarly communication0.0080.010
Open science0.0010.006
Research integrity0.0030.005
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 head0.062
GPT teacher head0.335
Teacher spread0.273 · 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 designNot applicable
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

Citations26
Published2008
Admission routes1
Has abstractyes

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