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 "theory in theory out the uses of social theory in machine learning for social science"):
  Abstract: Research at the intersection of machine learning and the social sciences has provided critical new insights into social behavior. At the same time, a variety of critiques have been raised ranging from technical issues with the data used and features constructed, problematic assumptions built into models, their limited interpretability, and their contribution to bias and inequality. We argue such issues arise primarily because of the lack of social theory at various stages of the model building and analysis. In the first half of this paper, we walk through how social theory can be used to answer the basic methodological and interpretive questions that arise at each stage of the machine learning pipeline. In the second half, we show how theory can be used to assess and compare the quality of different social learning models, including interpreting, generalizing, and assessing the fairness of models. We believe this paper can act as a guide for computer and social scientists alike to navigate the substantive questions involved in applying the tools of machine learning to social data.

Includes members:
  Member "50 years of test un fairness lessons for machine learning":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "demographic bias in biometrics a survey on an emerging challenge")
  Member "towards a critical race methodology in algorithmic fairness":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "theory in theory out how social theory can solve problems that machine learning can t")
  Member "racial categories in machine learning":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "theory in theory out how social theory can solve problems that machine learning can t")
  Member "garbage in garbage out do machine learning application papers in social computing report where human labeled training data comes from":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a hierarchy of limitations in machine learning")
  Member "privacy ethics and data access a case study of the fragile families challenge":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "theory in theory out how social theory can solve problems that machine learning can t")
  Member "an intersectional definition of fairness":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "theory in theory out how social theory can solve problems that machine learning can t")
  Member "automated hate speech detection and the problem of offensive language":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "ten social dimensions of conversations and relationships")
  Member "attention is all you need":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "using a thousand optimization tasks to learn hyperparameter search strategies")

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)