Based on my prior knowledge, the feature `foreign_worker` can be a relevant indicator for determining whether a person receives credit or not. Here's an analysis of its relationship with the target variable:

- If the value of `foreign_worker` is "yes", it indicates that the person is a foreign worker.
- Depending on the specific context and dataset, there can be different relationships between being a foreign worker and the likelihood of receiving credit. For example, in some cases, being a foreign worker might make it more difficult to receive credit due to potential visa restrictions or lack of credit history in the new country. In other cases, being a foreign worker might have no impact on credit approval. It's important to analyze the data and context to determine the relationship.

Based on this analysis, here is the dictionary with possible values of the `foreign_worker` feature for each target class:

```json
{
  "yes": ["yes"],
  "no": ["no"]
}
```
Note: This dictionary assumes that the feature `foreign_worker` only takes the values "yes" and "no". If there are other possible values, please provide the complete list, and I can update the dictionary accordingly.