Second-Birth Intentions of Married Women Based on Socioeconomic and Psychocultural Characteristics
Bibliographic record
Abstract
South Korea is a country affected by low fertility rates. The purpose of this study is to investigate if employment status of married women or other factors influence the intention of having a second child. One assumes that socio-cultural pressure exists for married couples to have at least one child but the decision whether to have a second child is personal preference. In determination of this personal preference, many variables are taken into consideration; social variables such as household incomes and husband employment status, cultural variables like parents instrumental value, and the expected gender of the second child. Because work life plays a large role in Korean society, parenting support variables are also taken into consideration, measured as the husbands level of participation in child rearing and their workplace parenting support system. Panel data from the Korea Institute of Child Care and Education in 2008 were analyzed using the logistic regression method. This data-set was limited to 677 parents currently having their first and only child. The data-set reveals that when faced with the high costs associated with rearing a second child, instability of husbands employment, or low expectation of the second childs gender-intention of subsequent births is markedly lower. In particular, unemployed women are prone to make a decision based on their economic status. It indicates that the Korean government should take differentiated intervention between employed and unemployed married women to overcome the low child birth rate.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".