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Record W2950795683 · doi:10.51657/ric.v4i1.40992

Concept of Will as an Open Problem in Culture-Historical Context

2017· article· en· W2950795683 on OpenAlexvenueno aff
Nataliya N. Tolstykh

Bibliographic record

VenueRevue internationale du CRIRES innover dans la tradition de Vygotsky · 2017
Typearticle
Languageen
FieldPsychology
TopicPsychology of Development and Education
Canadian institutionsnot available
Fundersnot available
KeywordsAppropriationProcess (computing)EpistemologyContext (archaeology)Cognitive scienceControl (management)Subject (documents)PsychologyCognitionSociologyComputer scienceNeurosciencePhilosophyHistoryArtificial intelligence

Abstract

fetched live from OpenAlex

Outlines a new approach to the problem of development of will, emanating from the tradition of thought represented by Vygotsky and Bozhovich. The main conceptual de-velopment lies in drawing a distinction between two concepts – will (volya) and goal appropriation, self-regulation, executive cognitive control of behavior (proyzvolnost’). Both concepts emphasize the readiness and ability of an individual to pursue a goal. The distinction lies in the nature of that goal determination. In will, it is self generated and comes from the inner world of the individual while in goal appropriation, it is determined by an external source but is readily appropriated. A such distinction is supported by re-cent findings in neuroscience which describe the actualization of di˙erent brain structures depending on whether an individual acts upon will or willingly submission. Hence, the personality development is considered as a process of will development in which will and goal appropriation inter plays and progresses in specific stages paving the way for subjunctivization or becoming a true subject of that culture.

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)0.004
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 score0.010
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0060.061
Scholarly communication0.0100.012
Open science0.0010.007
Research integrity0.0030.006
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 head0.051
GPT teacher head0.351
Teacher spread0.300 · 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

Citations3
Published2017
Admission routes1
Has abstractyes

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Same venueRevue internationale du CRIRES innover dans la tradition de VygotskySame topicPsychology of Development and EducationFrench-language works237,207