Upon initial analysis, it is difficult to determine the relationship between gender and the task of whether a person earns more than $50,000 per year. In general, gender may not directly impact an individual's income. However, it is important to note that gender can be a factor in employment opportunities and wage disparities, so it may indirectly influence earning potential. To analyze the relationship more thoroughly, we would need to gather and analyze data on individuals' earnings based on gender.

Based on the given information, the analysis indicates that we need to create a dictionary with gender values for each target class, "yes" and "no". Since we cannot predict which gender values are hard to predict without data, we will include all possible values for each target class in the dictionary.

Here is the requested dictionary in Markdown format:

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