Based on prior knowledge, the employment feature is likely to have some relationship with the target variable, as a person's employment may impact their ability to receive credit. However, without further data and analysis, it is difficult to ascertain the exact relationship and the values of the employment feature that are indicative of whether a person receives credit or not.

Here is a possible analysis for the given feature:

- Employment categories such as '>=7' or '4<=X<7' may indicate more stability and financial security, which could increase the chances of receiving credit.
- Being unemployed or having employment less than 1 year ('<1') may indicate a higher risk for the lender, reducing the chances of receiving credit.

Based on this analysis, we can create the dictionary as follows:

```json
{
	"yes": [">=7", "4<=X<7"],  
	"no": ["unemployed", "<1"]  
}
```

Please note that this analysis is based on general knowledge and assumptions. Without specific data or further analysis, the relationship between the employment feature and the target variable may not be accurately captured.