Based on the given feature "workclass" and the task of determining if a person earns more than 50000 dollars per year, we can analyze the relationship between the feature and the target variable as follows:

The workclass refers to the employment status of an individual. To determine if a person earns more than 50000 dollars per year, the workclass can be an important factor. Certain workclass categories may be more likely to earn higher incomes, while others may be more likely to earn lower incomes.

To analyze this relationship, we can consider the distribution of workclass categories for each target class (yes and no) and identify any noticeable patterns or differences.

Here is the dictionary with the specific details:

```json
{
	"no": ["Private", "Local-gov", "?", "Self-emp-not-inc", "Federal-gov", "State-gov", "Without-pay", "Never-worked"],
	"yes": ["Private", "Self-emp-not-inc", "Self-emp-inc", "Federal-gov", "Local-gov", "State-gov"]
}
```

In the target class "no" (earnings less than or equal to 50000 dollars per year), individuals can have any workclass, including "Private", "Local-gov", "?", "Self-emp-not-inc", "Federal-gov", "State-gov", "Without-pay", and "Never-worked".

In the target class "yes" (earnings more than 50000 dollars per year), individuals can have workclass categories such as "Private", "Self-emp-not-inc", "Self-emp-inc", "Federal-gov", "Local-gov", and "State-gov".

This analysis shows that individuals with certain workclass categories are more likely to earn more than 50000 dollars per year, while others may have a higher likelihood of earning less.

Please note that since the "?" category is included in both target classes, it seems to represent missing values or unknown workclass information.