```json
{
	"yes": ["none", "guarantor", "co applicant"],
	"no": ["none", "guarantor", "co applicant"]
}
```

Based on the given feature "other_parties" which specifies the presence of other debtors or guarantors, it appears that the feature can have three possible categories: "none", "guarantor", and "co applicant". These categories refer to the presence of other parties involved in the credit application.

To analyze the relationship between the feature and the target variable ("Does this person receive a credit? Yes or no?"), it is important to consider the potential influence of other debtors or guarantors on the credit decision. 

In this case, credit approval may depend on the presence or absence of other parties. For example, if there are no other parties involved ("none"), it might increase the likelihood of receiving a credit ("yes"). Conversely, if there is a guarantor or a co-applicant, it might increase the chances of the credit being rejected ("no"), as the presence of additional parties could potentially indicate a higher risk for the lender.

Therefore, it is reasonable to assume that the feature "other_parties" could have the same possible values for both the "yes" and "no" target classes: ["none", "guarantor", "co applicant"].

Please note that without further information or data analysis, it is difficult to guarantee the accuracy or completeness of this analysis. However, based on general knowledge and assumptions about credit approval processes, this dictionary provides a reasonable representation of the relationship between the "other_parties" feature and the target variable.