Automated Author ProfileLee, Soohyung
Lee, Soohyung
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 3.8 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This paper examines the possibility that a child's years of schooling could increase in the number of siblings, instead of being diminished by competition for parents' resources: if unable to finance the education of their younger children, parents may do so through their older children's labor income. We examine this possibility in a model combining convex returns to education and credit constraints. Our model predicts correlations among family size, years of schooling and birth order, which would not exist when either of these two elements is absent. Empirical patterns shown in the United States, Mexico, and South Korea support the model predictions.
Authors
- Lafortune, Jeanne ;
- Lee, Soohyung
This paper examines the possibility that a child's years of schooling could increase in the number of siblings, instead of being diminished by competition for parents' resources: if unable to finance the education of their younger children, parents may do so through their older children's labor income. We examine this possibility in a model combining convex returns to education and credit constraints. Our model predicts correlations among family size, years of schooling and birth order, which would not exist when either of these two elements is absent. Empirical patterns shown in the United States, Mexico, and South Korea support the model predictions.
Authors
- Lafortune, Jeanne ;
- Lee, Soohyung