Verification status: Author, title, publication, pagination or article identifier, and stable identifier fields were checked against publisher, DOI, arXiv, or OpenReview records where available. Principal source-to-claim uses were reviewed for scope. See the Citation Verification Audit.
Registry scope: This registry includes current article sources and supplementary reading retained for citation history. A bibliographic entry alone does not establish support for a particular CSI claim; the citations in each article identify the sources used for its explanations.
Emergence and multilevel theory
Chan, D. (1998). Functional relations among constructs in the same content domain at different levels of analysis: A typology of composition models. Journal of Applied Psychology, 83(2), 234–246. https://doi.org/10.1037/0021-9010.83.2.234
Morgeson, F. P., & Hofmann, D. A. (1999). The structure and function of collective constructs: Implications for multilevel research and theory development. Academy of Management Review, 24(2), 249–265. https://doi.org/10.5465/amr.1999.1893935
Kozlowski, S. W. J., & Klein, K. J. (2000). A multilevel approach to theory and research in organizations: Contextual, temporal, and emergent processes. In K. J. Klein & S. W. J. Kozlowski (Eds.), Multilevel theory, research, and methods in organizations: Foundations, extensions, and new directions (pp. 3–90). Jossey-Bass.
Kozlowski, S. W. J., Chao, G. T., Grand, J. A., Braun, M. T., & Kuljanin, G. (2013). Advancing multilevel research design: Capturing the dynamics of emergence. Organizational Research Methods, 16(4), 581–615. https://doi.org/10.1177/1094428113493119
Cattell, R. B. (1948). Concepts and methods in the measurement of group syntality. Psychological Review, 55(1), 48–63. https://doi.org/10.1037/h0055921
Goldstone, R. L., Roberts, M. E., & Gureckis, T. M. (2008). Emergent processes in group behavior. Current Directions in Psychological Science, 17(1), 10–15. https://doi.org/10.1111/j.1467-8721.2008.00539.x
Panzarasa, P., & Jennings, N. R. (2006). Collective cognition and emergence in multi-agent systems. In R. Sun (Ed.), Cognition and multi-agent interaction: From cognitive modeling to social simulation (pp. 401–408). Cambridge University Press.
Sawyer, R. K. (2000). Simulating emergence and downward causation in small groups. In S. Moss & P. Davidsson (Eds.), Multi-agent-based simulation (pp. 49–67). Springer. https://doi.org/10.1007/3-540-44561-7_4
Sawyer, R. K. (2004). The mechanisms of emergence. Philosophy of the Social Sciences, 34(2), 260–282. https://doi.org/10.1177/0048393103262553
Sawyer, R. K. (2005). Social emergence: Societies as complex systems. Cambridge University Press. https://doi.org/10.1017/CBO9780511734892
Construct validity, validation, and uncertainty
Supplementary reading retained for citation history; not used to support current Reference explanations.
Cronbach, L. J., & Meehl, P. E. (1955). Construct validity in psychological tests. Psychological Bulletin, 52(4), 281–302. https://doi.org/10.1037/h0040957
Supplementary reading retained for citation history; not used to support current Reference explanations.
Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56(2), 81–105. https://doi.org/10.1037/h0046016
Supplementary reading retained for citation history; not used to support current Reference explanations.
Messick, S. (1995). Validity of psychological assessment: Validation of inferences from persons’ responses and performances as scientific inquiry into score meaning. American Psychologist, 50(9), 741–749. https://doi.org/10.1037/0003-066X.50.9.741
Supplementary reading retained for citation history; not used to support current Reference explanations.
Gneiting, T., & Raftery, A. E. (2007). Strictly proper scoring rules, prediction, and estimation. Journal of the American Statistical Association, 102(477), 359–378. https://doi.org/10.1198/016214506000001437
Computational social science and relational evidence
Lazer, D., Pentland, A., Adamic, L., Aral, S., Barabási, A.-L., Brewer, D., Christakis, N., Contractor, N., Fowler, J., Gutmann, M., Jebara, T., King, G., Macy, M., Roy, D., & Van Alstyne, M. (2009). Computational social science. Science, 323(5915), 721–723. https://doi.org/10.1126/science.1167742
Moody, J., & White, D. R. (2003). Structural cohesion and embeddedness: A hierarchical concept of social groups. American Sociological Review, 68(1), 103–127. https://doi.org/10.2307/3088904
Kumar, S., Hamilton, W. L., Leskovec, J., & Jurafsky, D. (2018). Community interaction and conflict on the web. In Proceedings of the 2018 World Wide Web Conference (pp. 933–943). https://doi.org/10.1145/3178876.3186141
Recent computational neighbors (2024–2026)
Proutskova, P. (2026). Beyond call and response: Modelling reciprocal coordination in human–AI vocal ensembles. In Companion of the 2026 ACM International Conference on Multimodal Interaction. https://doi.org/10.1145/3776591.3837051
Riedl, C. (2026). Emergent coordination in multi-agent language models. ICLR 2026. https://arxiv.org/abs/2510.05174
Prabhu, N. R., Tsfasman, M., Oertel, C., Gerkmann, T., & Lehmann-Willenbrock, N. (2025). Dynamics of collective group affect: Group-level annotations and the multimodal modeling of convergence and divergence. IEEE Transactions on Affective Computing, 17(1), 1014–1029. https://doi.org/10.1109/TAFFC.2025.3643752
Supplementary reading retained for citation history; not used to support current Reference explanations.
Salami Pargoo, N., Akash, K., Misu, T., Zahedi, Z., Ortiz, J., & Zheng, Z. (2025). Reading the Room: Learning Group States Beyond Pooled Individual Signals. OpenReview manuscript submitted to ICLR 2026. https://openreview.net/forum?id=JylKfgaW2V
De Luca, V. M., Varni, G., & Passerini, A. (2026). Boosting team modeling through tempo–relational representation learning. Cognitive Computation, 18, Article 61. https://doi.org/10.1007/s12559-026-10581-y
Malyutina, H. (2026). BEHAVE: A Hybrid AI Framework for Real-Time Modeling of Collective Human Dynamics. arXiv preprint arXiv:2605.12730. https://doi.org/10.48550/arXiv.2605.12730
Lemos, M., Cardoso, P. J. S., & Rodrigues, J. M. F. (2026). MiE: A microscopic model for real-time group engagement estimation using gaze and posture. Journal of Computational Science, 96, 102856. https://doi.org/10.1016/j.jocs.2026.102856
Yeo, S., Zhang, T., Bateman, S., Hsieh, G., Kim, Y.-H., Perrault, S. T., Li, J., & Tang, A. (2026). Group conversational agents: A review of designs that support and shape group interaction. In Proceedings of the 2026 ACM Designing Interactive Systems Conference. https://doi.org/10.1145/3800645.3812934
Zhao, Y., Zhang, W., Sarkar, A., Rechkemmer, A., Merono Penuela, A., & Simperl, E. (2026). GenAI-Based Group Awareness Tools for Supporting Collaborative Learning. Human–Computer Interaction, accepted/in press. Publisher repository record.
Awareness and human–AI systems
Endsley, M. R. (1995). Toward a theory of situation awareness in dynamic systems. Human Factors, 37(1), 32–64. https://doi.org/10.1518/001872095779049543
Supplementary reading retained for citation history; not used to support current Reference explanations.
Amershi, S., Weld, D., Vorvoreanu, M., Fourney, A., Nushi, B., Collisson, P., Suh, J., Iqbal, S., Bennett, P. N., Inkpen, K., Teevan, J., Kikin-Gil, R., & Horvitz, E. (2019). Guidelines for human–AI interaction. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/3290605.3300233
O’Neill, T. A., McNeese, N. J., Barron, A., & Schelble, B. G. (2022). Human–autonomy teaming: A review and analysis of the empirical literature. Human Factors, 64(5), 904–938. https://doi.org/10.1177/0018720820960865
Registry maintenance
New records are added only after bibliographic and claim-use review. Corrections are recorded in the Version History and governed by the Editorial and Citation Policy. The current method and results are documented in the Citation Verification Audit.