Human Development in ASEAN Countries: A Comparative Semilogarithmic Analysis Between Countries
Bibliographic record
Abstract
This study compares the effectiveness of human development policies across ASEAN countries by analyzing each nation's unique context and characteristics.The goal is to identify the most suitable policies for improving human development and achieving the SDGs, particularly in narrowing disparities in human development in ASEAN countries.Therefore, the primary approach is to compare the estimation results of human development determinants for each ASEAN country using semilogarithmic equations.The data for this study were sourced from the World Bank and the United Nations Development Programme.This study finds that the effectiveness of policies varies significantly across countries.While economic growth has generally been associated with improved human development in most ASEAN countries, population growth has a negative impact in countries with large populations.Government spending has only been effective in Vietnam, and external factors such as trade openness and foreign direct investment have not yielded optimal results across all ASEAN sample countries.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".