Based on the given feature description, the feature "fnlwgt" represents the number of units in the target population that the responding unit represents. To analyze the relationship between this feature and the target variable (earning more than 50000 dollars per year), we need to consider our prior knowledge about income distribution.

Since there are no specific ranges provided for the feature values, we can assume that the feature values can vary widely. However, it is reasonable to expect that higher values of "fnlwgt" may correspond to individuals who earn more than 50000 dollars per year, as they may represent a larger portion of the target population.

To generate a dictionary with specific details, including typical "fnlwgt" values for each target class, we can analyze the relationship between the feature and the target using a dataset or statistical analysis. However, without additional information or access to data, we can only provide a generic example of the desired dictionary format:

```json
{
    "no": [2000, 3000, 4000, 5000, 6000],
    "yes": [8000, 9000, 10000, 11000, 12000]
}
```

Please note that these values are only hypothetical and do not represent any specific dataset. In a real analysis, it is necessary to analyze the feature-target relationship using actual data to generate more accurate and meaningful results.