Table 3.
Regression results of related variables.
| Title of high-level talent | Level of academic recognition | |||
|---|---|---|---|---|
| Coefficient (SE) | Odds ratio | Coefficient (SE) | Odds ratio | |
| Personality | ||||
| Age | −0.10*** (−3.55) | 0.90*** | 0.14*** (7.39) | 1.15*** |
| Hometown | 1.39*** (3.97) | 4.01*** | −0.03 (−0.14) | 0.97 |
| Gender | 0.39 (0.95) | 1.47 | 0.31 (0.96) | 1.36 |
| Human capital | ||||
| Initial academic degree | 1.04*** (4.67) | 2.83*** | 0.19 (1.16) | 1.21 |
| Final academic degree | 0.94*** (6.79) | 2.57*** | 0.75*** (6.84) | 2.12*** |
| Key university | 0.33* (1.67) | 1.40* | 0.23** (2.32) | 1.26** |
| Length of service in Guangxi | −0.03** (−1.98) | 0.97** | 0.00 (0.01) | 1.00 |
| Skills certificate | 0.18 (0.51) | 1.19 | 0.53** (2.30) | 1.70** |
| Cumulative advantage | ||||
| Professional qualification | −0.12 (−0.45) | 0.89 | 0.55** (2.50) | 1.73** |
| Overseas talent | 1.35 (1.24) | 3.85 | −0.81** (−2.29) | 0.45** |
| Number of national-level titles | 0.68** (2.02) | 1.97** | 0.38 (1.52) | 1.46 |
| Number of national-level funding | 3.15*** (2.72) | 23.38*** | 1.25*** (3.34) | 3.49*** |
| Number of provincial-level titles | 0.37 (1.20) | 1.45 | −0.96*** (−4.40) | 0.38*** |
| Fixed effects | ||||
| Location | 0.12* (1.66) | 1.13* | 0.09* (1.7998) | 1.09* |
| Professional field | 0.01 (0.49) | 1.01 | 0.07*** (3.45) | 1.07*** |
| Institution | −0.31*** (−2.68) | 0.73*** | −0.19** (−2.28) | 0.83** |
| Thresholds | ||||
| cut1 | 12.29*** (9.77) | 12.29*** | ||
| cut2 | 14.22*** (10.87) | 14.22*** | ||
| cut3 | 16.00*** (11.83) | 16.00*** | ||
| cut4 | 19.71*** (11.49) | 19.71*** | ||
| N | 499 | 499 | 499 | 499 |
| Pseudo R2 | 0.53 | 0.53 | 0.28 | 0.28 |
*
p < 0.10,
**
p < 0.05,
***
and p < 0.01.