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Record W1848659895 · doi:10.1177/0952695114560200

Deconstructing Vygotsky’s victimization narrative

2015· article· en· W1848659895 on OpenAlexaff
Jennifer Fraser, Anton Yasnitsky

Bibliographic record

VenueHistory of the Human Sciences · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Education and Learning Practices
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNarrativePersonaVariety (cybernetics)CommunismSociologySoviet unionPersonal narrativeGovernment (linguistics)AestheticsEpistemologyHistoryPsychoanalysisLawLiteraturePsychologyPolitical scienceArtPhilosophyHumanitiesLinguisticsPoliticsComputer science

Abstract

fetched live from OpenAlex

Although many facets of Lev Vygotsky’s life have drawn considerable attention from historians of science, perhaps the most popular feature of his personal narrative was that his work was actively chastised by the Stalinist government. Almost all contemporary references to Vygotsky’s personal history emphasize that from 1936 to 1956, it was forbidden to either discuss or disseminate any of Vygotsky’s works within the Soviet Union. Although this ‘Vygotsky ban’ is both widely acknowledged and frequently cited by a variety of scholars, the exact nature of this alleged Communist party censure has received far less historical attention. Through focusing on the logistics of Soviet ‘bans,’ this article attempts to shed light on this historical mystery and augment the growing body of revisionist literature that serves to deconstruct the mythologized persona of Lev Vygotsky.

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)0.005
metaresearch head score (Gemma)0.009
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: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0150.047
Scholarly communication0.0120.011
Open science0.0020.010
Research integrity0.0040.008
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 head0.260
GPT teacher head0.428
Teacher spread0.168 · 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

Citations15
Published2015
Admission routes1
Has abstractyes

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