From prior knowledge, we can assume that the feature "foreign_worker" can have an impact on whether a person receives credit or not. 

Analyzing the relationship between the "foreign_worker" feature and the task of receiving credit, we can make the following observations:

1. If a person is a foreign worker, they may have a lower chance of receiving credit due to factors such as limited credit history, visa restrictions, or potential difficulties in verifying their financial stability.
2. On the other hand, if a person is not a foreign worker, they may have a higher chance of receiving credit as they are likely to have a more established credit history and financial stability.

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

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

Explanation:
- For the target class "yes" (person receives credit), the possible values of the "foreign_worker" feature would be "no" (indicating the person is not a foreign worker).
- For the target class "no" (person does not receive credit), the possible values of the "foreign_worker" feature would be "yes" (indicating the person is a foreign worker).

Note: Since the original question did not mention any other possible values for the "foreign_worker" feature, we assume there are only "yes" and "no" as categories.