Based on the feature description and task, we can analyze the relationship between the feature "personal_status" and the target variable "Does this person receive a credit?".

From the given categories of personal_status:
- "male single" could imply that the person is not married and is single.
- "female div/dep/mar" could imply that the person is either divorced, separated, or married.
- "male div/sep" could imply that the person is either divorced or separated.
- "male mar/wid" could imply that the person is either married or widowed.

It is likely that personal_status could have some influence on whether a person receives credit or not. For example, being single might have a positive effect on receiving credit, while being divorced, separated, or widowed might have a negative effect.

Based on this analysis, the dictionary with the specific details would be as follows:

```json
{
	"yes": ["male single"],
	"no": ["female div/dep/mar", "male div/sep", "male mar/wid"]
}
```

Please note that this analysis considered only the given feature and the general understanding of personal_status. There may be additional factors that also influence the target variable, and a more detailed analysis could provide a better understanding of the relationship.