Exploration of Centralized and Decentralized Education Systems Around the World
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Through the use of the Program for International Student Assessment’s (PISA) Global Competence results, the Economic Intelligence Unit’s (EIU) Democracy Index ratings, and centralization-decentralization spectrum rubrics, this dissertation shows the association between level of democracy and education system, and the association of these variables with the global competence of a country. This study aims to answer two research questions: (1) To what extent is there an association between the level of democracy (full democracy, flawed democracy, hybrid regime, authoritarian regime) and the implementation of a centralized or decentralized education system? (2) To what extent does this association determine Global Competence scores? Global competence is determined through student-completed questionnaires and assessments that surround the concepts of knowledge, values, attitudes, and skills. Data were available for twenty-six countries for all three variables: Albania, Canada, Chile, Taiwan, Colombia, Costa Rica, Croatia, Greece, Hong Kong, Indonesia, Israel, Kazakhstan, Korea, Latvia, Lithuania, Malta, Morocco, Panama, Philippines, Russia, Scotland (UK), Serbia, Singapore, Slovakia, Spain, and Thailand. Secondary data analysis of two datasets (Global Competence results and Democracy Index ratings) were used in addition to research of public information of a country’s education system traits to complete the centralization-decentralization spectrum rubric. The Eta Coefficient shows a strong association between the governing person or people and the impact that has on the decision to implement a centralized or decentralized education system. A multiple regression analysis indicates that the Democracy Index and centralization-decentralization spectrum are associated with a country’s Global Competence results.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it