human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "fairness and decision making in collaborative shift scheduling systems"):
  Abstract: The strains associated with shift work decrease healthcare workers' well-being. However, shift schedules adapted to their individual needs can partially mitigate these problems. From a computing perspective, shift scheduling was so far mainly treated as an optimization problem with little attention given to the preferences, thoughts, and feelings of the healthcare workers involved. In the present study, we explore fairness as a central, human-oriented attribute of shift schedules as well as the scheduling process. Three in-depth qualitative interviews and a validating vignette study revealed that while on an abstract level healthcare workers agree on equality as the guiding norm for a fair schedule, specific scheduling conflicts should foremost be resolved by negotiating the importance of individual needs. We discuss elements of organizational fairness, including transparency and team spirit. Finally, we present a sketch for fair scheduling systems, summarizing key findings for designers in a readily usable way.

Includes members:
  Member "on the apparent conflict between individual and group fairness":
    also connected through other hyperedges:
      (none)
  Member "explaining models an empirical study of how explanations impact fairness judgment":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "questioning the ai informing design practices for explainable ai user experiences")
  Member "fairness in machine learning lessons from political philosophy":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "data and model dependencies of membership inference attack")
  Member "inherent trade offs in the fair determination of risk scores":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "algorithmic fairness")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.CY(Computers and Society)