Based on the given feature "foreign_worker" and the task of determining whether a person receives credit, we can conduct a thorough analysis of the relationship between the feature and the target variable.

From prior knowledge, we can assume that the "foreign_worker" feature may have some influence on whether a person receives credit. To analyze this relationship, we can look at the distribution of the feature values for each target class.

Here is an analysis of the relationship between the "foreign_worker" feature and the target variable:

For target class "yes" (person receives credit):
- Possible values of feature "foreign_worker": 'yes'

For target class "no" (person does not receive credit):
- Possible values of feature "foreign_worker": 'yes', 'no'

Based on this analysis, we can create the following dictionary:

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

Please note that this analysis assumes that the feature values 'yes' and 'no' are exhaustive and no other values are present in the dataset.