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Record W2293923363 · doi:10.14421/jpi.2015.41.49-70

Perbandingan Sistem Pendidikan di Tiga Negara; Mesir, Iran dan Turki

2015· article· en· W2293923363 on OpenAlexaboutno aff
Muhammad Nurul Ihsan

Bibliographic record

VenueJurnal Pendidikan Islam · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Islamic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceCurriculumEconomic growthForeign policyPopulationMiddle EastPoliticsGeographySociologyDemographyEconomicsLaw

Abstract

fetched live from OpenAlex

AbstractThis article discusses a comparative analysis of education in three countries where the population is predominantly of a Muslim background; Egypt, Iran and Turkey, andexplains about the system of education in primary schools, secondary schools and colleges.Additionally, this article clarifies the latest education policy, curriculum, subjects, andassessment systems in schools and universities. The three countries have some similarities;each country is implementing the policy of compulsory education with it split into threelevels. The other similarity being that is the students have a high interest for furtherstudy in foreign universities with some destination countries being: the United Statesof America, United Kingdom, Germany, Saudi Arabia, Canada, Ukraine, Malaysia,France, and Austria. Due to unfavorable politics in both countries of Egypt and Turkey, aswell as Iran, education has been effected by a foreign policy that is often contradictory.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.090
GPT teacher head0.347
Teacher spread0.257 · 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

Citations7
Published2015
Admission routes1
Has abstractyes

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