Based on prior knowledge, it is important to analyze the relationship between race and the income level to determine if race plays a role in earning more than $50,000 per year.

To conduct this analysis, we can examine the proportion of each race category within the target classes of "yes" and "no". By comparing the distribution of race categories in both target classes, we can identify potential relationships that may exist.

Once the analysis is complete, we can create a dictionary with the required format. Here's the dictionary for the given feature:

```json
{
	"no": ["Black", "Asian-Pac-Islander", "Other", "Amer-Indian-Eskimo"],  
	"yes": ["White"]
}
```

In this case, the race values "Black", "Asian-Pac-Islander", "Other", and "Amer-Indian-Eskimo" are associated with the target class "no," while the race value "White" is associated with the target class "yes."