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Record W4390316134 · doi:10.5281/zenodo.10394211

Comparison of Turkey and the Countries with High PISA Success South Korea, Finland and Canada in Terms of Transition Education Levels

2023· article· en· W4390316134 on OpenAlexaboutno aff
İlknur Maya, Sedat YAKUT

Bibliographic record

VenueDergiPark (Istanbul University) · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Educational Reforms and Inequalities
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyPolitical scienceDemographySocioeconomicsEconomicsSociology

Abstract

fetched live from OpenAlex

It is aimed to compare the countries of South Korea, Finland and Canada, which are highly successful in PISA exam, and Turkey in terms of the transition system between educational levels. Document analysis method was used in the study. In the universe of the study, there are thirty-eight countries from the Organization for Economic Cooperation and Development. Turkey and the countries of South Korea, Canada and Finland which are profoundly effective in PISA, constitute the sample of the study. According to the results of the study, it has been determined that there are no exams in transition from pre-school education to primary education in Turkey, Canada, Finland and South Korea. There is a strict examination in the transition system from primary to secondary education level in South Korea, while there are no central exams in Canada and Finland, and transition to secondary education is made according to secondary school student success. In Turkey, a central examination is held for the transition from primary to secondary education level or students are accepted to secondary education by local placement, considering the addresses of the students according to their success. In Turkey and South Korea, a central exam is applied in the transition system from secondary education to higher education.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.625
Threshold uncertainty score0.352

Codex and Gemma teacher scores by category

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

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 head0.014
GPT teacher head0.260
Teacher spread0.246 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2023
Admission routes1
Has abstractyes

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