The Policy Research for the Improvement of Excessive Marriage Expense in South Korea
Bibliographic record
Abstract
Excessive marriage-related expenses have become a serious social problem in South Korea. This has led to marriage delay, a low birthrate, the acceleration of an aging society, decreased national economic growth, and employment problems, among others. In South Korea, the young unmarried men and women cannot adequately prepare to shoulder the excessive expenses related to getting married in the future, as well as the high cost of purchasing a house. In fact, almost all of them are being supported by their parents in their marriage preparations or have secured a loan for such purposes. Small weddings and desirable consumption are thus aggressively being promoted for the prevention of excessive marriage-related expenses in South Korea. The reality, however, is very different. In this study, 1,000 persons (500 men, 500 women) in Seoul, South Korea with less than 5 years of marriage were surveyed for the analysis of excessive marriage-related expenses. The analysis results show that marriage expense support has long-term reciprocity and is statistically significant. The economic support beneficiary model is statistically significant both among the men and the women for childcare, housework, and economic support provision. The economic support provision model, on the other hand, is statistically significant among both the men and the women in terms of housework support.This paper discusses and presents the policy direction for addressing the problem of excessive marriage-related expenses in South Korea. It is believed that the policy direction proposed by this study will also have global implications and will become useful for addressing the problem of excessive marriage-related expenses through research result sharing.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".