To analyze the relationship between the gender feature and the task of whether a person earns more than 50000 dollars per year, we can look at the distribution of gender among the two target classes: yes and no.

By examining the data, we can create a dictionary that captures the possible values of the gender feature for each target class.

Here is the dictionary:

```json
{
	"no": ["Male", "Female"],
	"yes": ["Male", "Female"]
}
```

Since gender is a categorical variable, it can take two values: Male and Female. Both of these gender values are possible for both the "no" and "yes" target classes.