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Record W1876226365 · doi:10.5539/ies.v8n6p171

The Humanistic Approach to Upbringing and Education in the Creative Legacy of the Ukrainian Pedagogues of the Second Half of the 19th Century

2015· article· en· W1876226365 on OpenAlexvenueno aff
Іван Аносов, Mark Veniaminovych Elkin, Marina Mykhaylivna Golovkova, Ангеліна Коробченко, Mykola Mykolayovych Oksa

Bibliographic record

VenueInternational Education Studies · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Social Development in Ukraine
Canadian institutionsnot available
Fundersnot available
KeywordsUkrainianHumanismPedagogySociologyPersonalityHumanistic psychologyHumanistic educationEducation theorySocial scienceHigher educationPsychologyPolitical scienceSocial psychologyLawPhilosophy

Abstract

fetched live from OpenAlex

The article is dedicated to the study of the humanistic approach to upbringing and education in the creative legacy of the Ukrainian pedagogues of the second half of the 19th century. Through the analysis of S. Myropolskiy’s and Kh. Alchevska’s pedagogical legacy, a world outlook position of scholars concerning humanisation of the educational process is shown. In the course of the research, it is found out that basis of S. Myropolskiy’s and Kh. Alchevska’s conception was formed by the principles, confirmed by humanistic pedagogy. They revealed the humane approach essence to realizing the educational process in the national school. It is established that the pedagogues considered the teacher’s personality as an important figure of the human upbringing process.

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)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.022
Scholarly communication0.0060.002
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.107
GPT teacher head0.432
Teacher spread0.326 · 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 designQualitative
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
Published2015
Admission routes1
Has abstractyes

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