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Record W4390405323 · doi:10.58830/ozgur.pub383.c1702

Holistic Education

2023· book-chapter· en· W4390405323 on OpenAlexaboutno aff
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Bibliographic record

VenueÖzgür Yayınları eBooks · 2023
Typebook-chapter
Languageen
FieldSocial Sciences
TopicValues and Moral Education
Canadian institutionsnot available
Fundersnot available
KeywordsHolistic educationHolistic managementMillerHolistic healthPsychologyPedagogyCurriculumSociologyEngineering ethicsEngineeringPolitical scienceEcologyBiology

Abstract

fetched live from OpenAlex

The holistic approach emphasizes the development of active relationships at all levels. This relationship can be between individuals, between peer groups or between the individual and society. Recent research on holistic education and learning shows that the holistic approach has begun beginning to be emphasized. The holistic approach is usually focused on values education and management. The holistic approach entered the literature in the 1980s when Canadian scholar John P. Miller published “The holistic curriculum”. It can therefore be concluded that the holistic approach is based on the fact that the knowledge and skills to be acquired are related to others in the integrity of life, both in terms of content and design, and that the individual perceives the whole earlier and more easily.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.033
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0330.006

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 head0.144
GPT teacher head0.394
Teacher spread0.250 · 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
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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