The attributes sensitive for fairness analysis are:

1. **case:citizen**: This attribute indicates whether a person is a citizen or not, which may lead to discriminatory practices or biases in the process.
2. **case:gender**: This attribute may lead to biases or stereotypes in the process, for example, if male applicants are treated differently than female applicants.
3. **case:german speaking**: If German-speaking individuals receive preferential treatment or have different outcomes compared to non-German-speaking individuals, this attribute may be sensitive to fairness analysis.
4. **case:married**: This attribute may lead to biases or stereotypes in the process, for example, if married applicants are treated differently than single applicants.
5. **resource**: This attribute, which indicates the role of an individual performing an activity (e.g., Tenant, Real Estate Agent), may lead to biases or stereotypes in the process, for example, if certain roles are given more or less attention than others.

These attributes have the potential to introduce biases or unfairness in the process, and analyzing them could be essential for ensuring fairness and non-discrimination.