Toward One Korea Examination of Early Childhood Education and Care in South and North Korea
Bibliographic record
Abstract
The two Koreas, the South and the North, differ drastically in what seem to be the most fundamental of ways, Many Koreans still, however, hold hope for a unified homeland and therefore important to examine the inevitably problematic issues in early childhood education and care that will be encountered when the two Koreas are unified. The institutions of early childhood education and care on each side of the DMZ evolved under different ideologies and organizational principles each ideology promoted. The issue of early childhood education and care, which is directly linked to every nation`s future, will be especially difficult to bridge between a North that uses early childhood education and care as one of its main tools for maintaining Its communist system and a South that understands early childhood education and care in a more private context as part of an open competitive system. Given these disparities, preparation for an early childhood education and care post-unification era framework must begin now. Therefore, this research presents a direction for post-unification early childhood education and care by comparing and analyzing how the systems were developed on both sides of the peninsula following the division of Korea. To this end, South Korean and North Korean early childhood education and care ideologies legal systems, administrative systems, management policies, enrollment rates, costs, early childhood, teacher, policies and operating practices are scrutinized,
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".