Based on the given feature description and task, the feature "employment" is a categorical variable indicating the length of present employment in years. The feature categories are as follows: ['>=7', '1<=X<4', '4<=X<7', 'unemployed', '<1'].

To determine the relationship between the feature "employment" and the task of whether a person receives credit or not, we can analyze the distribution of employment categories among the two target classes (yes and no).

Here is the dictionary detailing the possible values of the feature "employment" for each target class:

```json
{
	"yes": [">=7", "unemployed"],
	"no": ["1<=X<4", "4<=X<7", "<1"]
}
```

According to the analysis, people who have been employed for a longer duration (>=7 years) or are currently unemployed have a higher chance of receiving credit (target class "yes"). On the other hand, people with shorter employment durations (1-3 years, 4-6 years, and less than 1 year) have a higher chance of not receiving credit (target class "no").