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Record W3096663646 · doi:10.5539/mas.v14n11p1

Democracy in Education between Reality and Aspirations: Palestine as a Model

2020· article· en· W3096663646 on OpenAlexvenueno aff
Mohammad Awad Shuibat

Bibliographic record

VenueModern Applied Science · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicJewish and Middle Eastern Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDemocracyContext (archaeology)CriticismPalestineSociologyProcess (computing)Democratic educationPolitical sciencePublic administrationPoliticsLawComputer science

Abstract

fetched live from OpenAlex

The research aims to study “education democracy " in terms of democratic practices in the educational process, developing a spirit of criticism, plurality of opinions, tolerance towards the opinions of others, respecting the decision of the majority and taking responsibility for the decision. In addition to the relationship between democracy and education, the relationship between democracy and education as a practice, and clarifying the goals of education for democracy, and clarifying areas of democratic awareness, the implications of education for democracy and procedures for developing democratic practices in education and the detection of obstacles to democratic practices in the educational process, and that is in the context of an applied analytical and scientific study based on the researcher's visit to Palestinian educational institutions and his knowledge of their reality, through which the researcher seeks to present what is hoped from the "education democracy" and how should it be applied to reality and what goals should these institutions seek to achieve?

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.042

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 studies0.0060.015
Scholarly communication0.0080.005
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.102
GPT teacher head0.342
Teacher spread0.240 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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